{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/srmaxey/Documents/Research/Classification/submission/replication/log.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}28 Jun 2024, 17:08:45

{com}. do "/var/folders/xj/2zvh3mps3b99bd1rgq00w3tc0000gn/T//SD52136.000000"
{txt}
{com}. *Replication code for "Democracy and Documents" submission to R&P
. 
. *This file replicates the results included in the main text and appendix.
. 
. version 18.0
{txt}
{com}. clear all
{res}{txt}
{com}. estimates clear
{txt}
{com}. 
. *Set command directory to location where replication files are saved.
. cd "/Users/srmaxey/Documents/Research/Classification/submission/replication/"
{res}/Users/srmaxey/Documents/Research/Classification/submission/replication
{txt}
{com}. 
. ********************************************************************************
. *PRETEST ANALYSIS
. ********************************************************************************
. use "pretest.dta", clear
{txt}
{com}. 
. ***Clean Data
. *Check for and delete responses that do not meet the inclusion criteria. This includes:
. 
.         *Unfinished surveys
.         tab finished

   {txt}Finished {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        176      100.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        176      100.00
{txt}
{com}.         
.         *Non-consenting surveys
.         tab consent

    {txt}consent {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        170       98.27       98.27
{txt}          2 {c |}{res}          3        1.73      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        173      100.00
{txt}
{com}.         drop if consent!=1
{txt}(6 observations deleted)

{com}.         tab consent

    {txt}consent {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        170      100.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        170      100.00
{txt}
{com}.         
.         *Participants flagged as bots by Qualtrics:
.                 *q_recaptchascore<0.5
.                 tab q_recaptchascore 

{txt}Q_Recaptcha {c |}
      Score {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
         .8 {c |}{res}         10        5.88        5.88
{txt}         .9 {c |}{res}         58       34.12       40.00
{txt}          1 {c |}{res}        102       60.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        170      100.00
{txt}
{com}.                 
.                 *q_relevantidduplicatescore==1
.                 tab q_relevantidduplicatescore

{txt}Q_RelevantI {c |}
DDuplicateS {c |}
       core {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        169      100.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        169      100.00
{txt}
{com}.                 drop if q_relevantidduplicatescore!=0
{txt}(1 observation deleted)

{com}.                 tab q_relevantidduplicatescore

{txt}Q_RelevantI {c |}
DDuplicateS {c |}
       core {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        169      100.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        169      100.00
{txt}
{com}.                 
.                 *q_relevantidfraudscore>=70
.                 tab q_relevantidfraudscore 

{txt}Q_RelevantI {c |}
DFraudScore {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        160       94.67       94.67
{txt}          5 {c |}{res}          7        4.14       98.82
{txt}         25 {c |}{res}          2        1.18      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        169      100.00
{txt}
{com}.         
.         *Participants using a VPS or otherwise not in the US
.                 *ip_block==1
.                 tab ip_block 

   {txt}IP_block {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        169      100.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        169      100.00
{txt}
{com}. 
. *Assess data quality via attention check
. tab attention1 

 {txt}attention1 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}          3        1.78        1.78
{txt}        1,2 {c |}{res}        151       89.35       91.12
{txt}          2 {c |}{res}          7        4.14       95.27
{txt}          3 {c |}{res}          4        2.37       97.63
{txt}          4 {c |}{res}          1        0.59       98.22
{txt}          5 {c |}{res}          3        1.78      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        169      100.00
{txt}
{com}.                 
. ***Create treatment and outcome variables
. gen decision=.
{txt}(169 missing values generated)

{com}. local decisionvars security_decision economic_decision domestic_decision
{txt}
{com}.         foreach d of local decisionvars {c -(}
{txt}  2{com}.                 replace decision=1 if `d'==1
{txt}  3{com}.                 replace decision=2 if `d'==2
{txt}  4{com}.                 replace decision=3 if `d'==3
{txt}  5{com}.                 replace decision=4 if `d'==4
{txt}  6{com}.                 {c )-}
{txt}(5 real changes made)
(10 real changes made)
(16 real changes made)
(24 real changes made)
(8 real changes made)
(25 real changes made)
(16 real changes made)
(7 real changes made)
(15 real changes made)
(18 real changes made)
(16 real changes made)
(9 real changes made)

{com}.         tab decision

   {txt}decision {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         28       16.57       16.57
{txt}          2 {c |}{res}         53       31.36       47.93
{txt}          3 {c |}{res}         48       28.40       76.33
{txt}          4 {c |}{res}         40       23.67      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        169      100.00
{txt}
{com}. 
. *For ease of analysis, create a binary version of the decision variable. Call it decisionbi.
. gen decisionbi=.
{txt}(169 missing values generated)

{com}.         replace decisionbi=0 if decision==1|decision==2
{txt}(81 real changes made)

{com}.         replace decisionbi=1 if decision==3|decision==4
{txt}(88 real changes made)

{com}. tab decisionbi

 {txt}decisionbi {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}         81       47.93       47.93
{txt}          1 {c |}{res}         88       52.07      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        169      100.00
{txt}
{com}. 
. *Create a dummy variable for each treatment condition. Call them security, economic, domestic.
. gen security=0
{txt}
{com}.         replace security=1 if security_decision==1|security_decision==2|security_decision==3|security_decision==4
{txt}(55 real changes made)

{com}. tab security

   {txt}security {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        114       67.46       67.46
{txt}          1 {c |}{res}         55       32.54      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        169      100.00
{txt}
{com}. 
. gen economic=0
{txt}
{com}.         replace economic=1 if economic_decision==1|economic_decision==2|economic_decision==3|economic_decision==4
{txt}(56 real changes made)

{com}. tab economic

   {txt}economic {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        113       66.86       66.86
{txt}          1 {c |}{res}         56       33.14      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        169      100.00
{txt}
{com}. 
. gen domestic=0
{txt}
{com}.         replace domestic=1 if domestic_decision==1|domestic_decision==2|domestic_decision==3|domestic_decision==4
{txt}(58 real changes made)

{com}. tab domestic

   {txt}domestic {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        111       65.68       65.68
{txt}          1 {c |}{res}         58       34.32      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        169      100.00
{txt}
{com}. 
. ***Analysis
. *Comparisons of proportion appropriate between treatment conditions (binary dv)
. prtest decisionbi if security==1|economic==1, by(security) 

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}      56
                                                   1{txt}: Number of obs = {res}      55
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .4107143{col 28} .0657414{col 58} .2818635{col 70}  .539565
           {txt}1 {c |}{res}{col 17} .7272727{col 28} .0600526{col 58} .6095719{col 70} .8449736
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.3165584{col 28} .0890407{col 58}-.4910749{col 70}-.1420419
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28}  .094049{col 38}   -3.37{col 49}0.001
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -3.3659
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0004         {txt}Pr(|Z| > |z|) = {res}0.0008          {txt}Pr(Z > z) = {res}0.9996
{txt}
{com}. prtest decisionbi if security==1|domestic==1, by(security)

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}      58
                                                   1{txt}: Number of obs = {res}      55
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .4310345{col 28} .0650257{col 58} .3035865{col 70} .5584825
           {txt}1 {c |}{res}{col 17} .7272727{col 28} .0600526{col 58} .6095719{col 70} .8449736
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.2962382{col 28} .0885136{col 58}-.4697216{col 70}-.1227548
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0930342{col 38}   -3.18{col 49}0.001
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -3.1842
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0007         {txt}Pr(|Z| > |z|) = {res}0.0015          {txt}Pr(Z > z) = {res}0.9993
{txt}
{com}. prtest decisionbi if economic==1|domestic==1, by(economic) 

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}      58
                                                   1{txt}: Number of obs = {res}      56
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .4310345{col 28} .0650257{col 58} .3035865{col 70} .5584825
           {txt}1 {c |}{res}{col 17} .4107143{col 28} .0657414{col 58} .2818635{col 70}  .539565
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0203202{col 28} .0924677{col 58}-.1609131{col 70} .2015535
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28}  .092498{col 38}    0.22{col 49}0.826
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res}  0.2197
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.5869         {txt}Pr(|Z| > |z|) = {res}0.8261          {txt}Pr(Z > z) = {res}0.4131
{txt}
{com}. 
. *Comparisons of means appropriate between treatment conditions (4-point dv)
. ttest decision if security==1|economic==1, by(security)

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}     56{col 22} 2.392857{col 34} .1186465{col 46} .8878692{col 58} 2.155084{col 70}  2.63063
       {txt}1 {c |}{res}{col 12}     55{col 22} 3.072727{col 34} .1344763{col 46} .9973028{col 58} 2.803119{col 70} 3.342336
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    111{col 22}  2.72973{col 34} .0948691{col 46} .9995085{col 58} 2.541721{col 70} 2.917738
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.6798701{col 34} .1791459{col 58}-1.034932{col 70}-.3248087
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -3.7951
{txt}H0: diff = 0                                     Degrees of freedom = {res}     109

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0001         {txt}Pr(|T| > |t|) = {res}0.0002          {txt}Pr(T > t) = {res}0.9999
{txt}
{com}. ttest decision if security==1|domestic==1, by(security)

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}     58{col 22} 2.327586{col 34} .1355858{col 46} 1.032591{col 58}  2.05608{col 70} 2.599092
       {txt}1 {c |}{res}{col 12}     55{col 22} 3.072727{col 34} .1344763{col 46} .9973028{col 58} 2.803119{col 70} 3.342336
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    113{col 22} 2.690265{col 34}  .101412{col 46} 1.078024{col 58} 2.489331{col 70}   2.8912
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.7451411{col 34} .1911422{col 58}-1.123902{col 70}  -.36638
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -3.8984
{txt}H0: diff = 0                                     Degrees of freedom = {res}     111

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0001         {txt}Pr(|T| > |t|) = {res}0.0002          {txt}Pr(T > t) = {res}0.9999
{txt}
{com}. ttest decision if economic==1|domestic==1, by(economic)

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}     58{col 22} 2.327586{col 34} .1355858{col 46} 1.032591{col 58}  2.05608{col 70} 2.599092
       {txt}1 {c |}{res}{col 12}     56{col 22} 2.392857{col 34} .1186465{col 46} .8878692{col 58} 2.155084{col 70}  2.63063
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    114{col 22} 2.359649{col 34} .0899613{col 46} .9605234{col 58}  2.18142{col 70} 2.537879
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0652709{col 34} .1806465{col 58}-.4231989{col 70}  .292657
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -0.3613
{txt}H0: diff = 0                                     Degrees of freedom = {res}     112

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.3593         {txt}Pr(|T| > |t|) = {res}0.7185          {txt}Pr(T > t) = {res}0.6407
{txt}
{com}. 
. *Create Figure 1
. mean decisionbi if security==1
{res}
{txt}{col 1}Mean estimation{col 45}{lalign 13:Number of obs}{col 58} = {res}{ralign 2:55}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 2}decisionbi {c |}{col 14}{res}{space 2} .7272727{col 26}{space 2} .0606061{col 37}{space 5} .6057649{col 51}{space 3} .8487806
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store security
{txt}
{com}. mean decisionbi if economic==1
{res}
{txt}{col 1}Mean estimation{col 45}{lalign 13:Number of obs}{col 58} = {res}{ralign 2:56}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 2}decisionbi {c |}{col 14}{res}{space 2} .4107143{col 26}{space 2} .0663363{col 37}{space 5} .2777733{col 51}{space 3} .5436553
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store economic
{txt}
{com}. mean decisionbi if domestic==1
{res}
{txt}{col 1}Mean estimation{col 45}{lalign 13:Number of obs}{col 58} = {res}{ralign 2:58}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 2}decisionbi {c |}{col 14}{res}{space 2} .4310345{col 26}{space 2} .0655936{col 37}{space 5} .2996855{col 51}{space 3} .5623834
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store domestic
{txt}
{com}. coefplot security economic domestic, vertical xlabel(none) /// 
>         ylabel(0(.2)1) ytitle("Proportion Appropriate") /// 
>         legend(rows(1)) scheme(s1mono) /// 
>         note("Figure compares the proportions of respondents who viewed the decision to classify the document as" /// 
>         "appropriate across treatment conditions with 95% confidence intervals. The figure uses a binary measure of" /// 
>         "appropriateness and data from the survey pretest.", span)
{res}{txt}
{com}. 
. ********************************************************************************
. *MAIN SURVEY ANALYSIS
. ********************************************************************************
. *Load Data
. use "mainsurvey.dta", clear
{txt}
{com}. 
. ***Clean Data
. *Check for and delete responses that do not meet the pre-registered inclusion criteria. This includes:
. *consent
.         tab consent

    {txt}consent {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        665       95.55       95.55
{txt}          2 {c |}{res}         31        4.45      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        696      100.00
{txt}
{com}.         drop if consent!=1
{txt}(54 observations deleted)

{com}.         tab consent

    {txt}consent {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        665      100.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        665      100.00
{txt}
{com}.         
.         *completed
.         tab finished

   {txt}Finished {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}         20        3.01        3.01
{txt}          1 {c |}{res}        645       96.99      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        665      100.00
{txt}
{com}.         drop if finished!=1
{txt}(20 observations deleted)

{com}.         tab finished

   {txt}Finished {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        645      100.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        645      100.00
{txt}
{com}.         
.         *attention screener
.         tab attention1

 {txt}attention1 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        104       16.12       16.12
{txt}          2 {c |}{res}          4        0.62       16.74
{txt}          3 {c |}{res}        537       83.26      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        645      100.00
{txt}
{com}.         keep if attention1==3
{txt}(108 observations deleted)

{com}.         tab attention1

 {txt}attention1 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          3 {c |}{res}        537      100.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        537      100.00
{txt}
{com}.         
.         *location requirements
.         tab ip_block

   {txt}IP_block {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        529       98.51       98.51
{txt}          1 {c |}{res}          7        1.30       99.81
{txt}          2 {c |}{res}          1        0.19      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        537      100.00
{txt}
{com}.         keep if ip_block==0
{txt}(8 observations deleted)

{com}.         tab ip_block

   {txt}IP_block {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        529      100.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        529      100.00
{txt}
{com}.         
.         tab ip_country

   {txt}IP_country {c |}      Freq.     Percent        Cum.
{hline 14}{c +}{hline 35}
United States {c |}{res}        529      100.00      100.00
{txt}{hline 14}{c +}{hline 35}
        Total {c |}{res}        529      100.00
{txt}
{com}.         keep if ip_country=="United States"
{txt}(0 observations deleted)

{com}.         tab ip_country

   {txt}IP_country {c |}      Freq.     Percent        Cum.
{hline 14}{c +}{hline 35}
United States {c |}{res}        529      100.00      100.00
{txt}{hline 14}{c +}{hline 35}
        Total {c |}{res}        529      100.00
{txt}
{com}.         
.         *Qualtrics bot detection
.         tab q_ballotboxstuffing 
{txt}no observations

{com}.         
.         tab q_recaptchascore 

   {txt}Q_RecaptchaScore {c |}      Freq.     Percent        Cum.
{hline 20}{c +}{hline 35}
         .699999988 {c |}{res}          1        0.19        0.19
{txt}         .800000012 {c |}{res}         20        3.80        3.98
{txt}0.10000000149011612 {c |}{res}          1        0.19        4.17
{txt} 0.8999999761581421 {c |}{res}        170       32.26       36.43
{txt}                  1 {c |}{res}        335       63.57      100.00
{txt}{hline 20}{c +}{hline 35}
              Total {c |}{res}        527      100.00
{txt}
{com}.         
.         tab q_relevantidduplicatescore 

{txt}Q_RelevantI {c |}
DDuplicateS {c |}
       core {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        526       99.62       99.62
{txt}        100 {c |}{res}          2        0.38      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        528      100.00
{txt}
{com}.         drop if q_relevantidduplicatescore>=75
{txt}(3 observations deleted)

{com}.         tab q_relevantidduplicatescore

{txt}Q_RelevantI {c |}
DDuplicateS {c |}
       core {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        526      100.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        526      100.00
{txt}
{com}.         
.         tab q_relevantidfraudscore 

{txt}Q_RelevantI {c |}
DFraudScore {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        496       94.30       94.30
{txt}          5 {c |}{res}         17        3.23       97.53
{txt}         10 {c |}{res}          1        0.19       97.72
{txt}         20 {c |}{res}          3        0.57       98.29
{txt}         25 {c |}{res}          5        0.95       99.24
{txt}         30 {c |}{res}          1        0.19       99.43
{txt}         50 {c |}{res}          3        0.57      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        526      100.00
{txt}
{com}.         drop if q_relevantidfraudscore>=30
{txt}(4 observations deleted)

{com}.         tab q_relevantidfraudscore

{txt}Q_RelevantI {c |}
DFraudScore {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        496       95.02       95.02
{txt}          5 {c |}{res}         17        3.26       98.28
{txt}         10 {c |}{res}          1        0.19       98.47
{txt}         20 {c |}{res}          3        0.57       99.04
{txt}         25 {c |}{res}          5        0.96      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. *Assess data quality via second attention check
. tab attention2

 {txt}attention2 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}          4        0.77        0.77
{txt}        1,2 {c |}{res}        502       96.17       96.93
{txt}          2 {c |}{res}          8        1.53       98.47
{txt}          3 {c |}{res}          4        0.77       99.23
{txt}          4 {c |}{res}          2        0.38       99.62
{txt}          5 {c |}{res}          2        0.38      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. ***Create Treatment and Outcome Variables
. 
. *Stage One: Confidence in institutions, binary
.         tab institutions

{txt}institution {c |}
          s {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         68       13.03       13.03
{txt}          2 {c |}{res}        132       25.29       38.31
{txt}          3 {c |}{res}        239       45.79       84.10
{txt}          4 {c |}{res}         83       15.90      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         gen institutionsbi=.
{txt}(522 missing values generated)

{com}.                 replace institutionsbi=0 if institutions==1|institutions==2
{txt}(200 real changes made)

{com}.                 replace institutionsbi=1 if institutions==3|institutions==4
{txt}(322 real changes made)

{com}.         tab institutionsbi

{txt}institution {c |}
        sbi {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        200       38.31       38.31
{txt}          1 {c |}{res}        322       61.69      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
. *Stage One: Trust in president, binary
.         tab trustpres

  {txt}trustpres {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         99       18.97       18.97
{txt}          2 {c |}{res}        129       24.71       43.68
{txt}          3 {c |}{res}        215       41.19       84.87
{txt}          4 {c |}{res}         79       15.13      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         gen trustpresbi=.
{txt}(522 missing values generated)

{com}.                 replace trustpresbi=0 if trustpres==1|trustpres==2
{txt}(228 real changes made)

{com}.                 replace trustpresbi=1 if trustpres==3|trustpres==4
{txt}(294 real changes made)

{com}.         tab trustpresbi

{txt}trustpresbi {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        228       43.68       43.68
{txt}          1 {c |}{res}        294       56.32      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. *Stage One: Trust in Congress, binary
.         tab trustcongress

{txt}trustcongre {c |}
         ss {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         94       18.01       18.01
{txt}          2 {c |}{res}        154       29.50       47.51
{txt}          3 {c |}{res}        223       42.72       90.23
{txt}          4 {c |}{res}         51        9.77      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         gen trustcongressbi=.
{txt}(522 missing values generated)

{com}.                 replace trustcongressbi=0 if trustcongress==1|trustcongress==2
{txt}(248 real changes made)

{com}.                 replace trustcongressbi=1 if trustcongress==3|trustcongress==4
{txt}(274 real changes made)

{com}.         tab trustcongressbi

{txt}trustcongre {c |}
       ssbi {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        248       47.51       47.51
{txt}          1 {c |}{res}        274       52.49      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. *Stage Two: Support for Firing
.         *4-point scale
.         gen fire=.
{txt}(522 missing values generated)

{com}.         local firevars fire_mil fire_fso
{txt}
{com}.         foreach f of local firevars {c -(}
{txt}  2{com}.                 replace fire=1 if `f'==1
{txt}  3{com}.                 replace fire=2 if `f'==2
{txt}  4{com}.                 replace fire=3 if `f'==3
{txt}  5{com}.                 replace fire=4 if `f'==4
{txt}  6{com}.                 {c )-}
{txt}(20 real changes made)
(53 real changes made)
(121 real changes made)
(66 real changes made)
(30 real changes made)
(36 real changes made)
(110 real changes made)
(86 real changes made)

{com}.         tab fire

       {txt}fire {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         50        9.58        9.58
{txt}          2 {c |}{res}         89       17.05       26.63
{txt}          3 {c |}{res}        231       44.25       70.88
{txt}          4 {c |}{res}        152       29.12      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
.         *Binary
.                 gen firebi=.
{txt}(522 missing values generated)

{com}.                 replace firebi=0 if fire==1|fire==2
{txt}(139 real changes made)

{com}.                 replace firebi=1 if fire==3|fire==4
{txt}(383 real changes made)

{com}.         tab firebi

     {txt}firebi {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        139       26.63       26.63
{txt}          1 {c |}{res}        383       73.37      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. *Stage Two: Trust Official
.         *4-point scale
.         gen trustofficial=.
{txt}(522 missing values generated)

{com}.         local trustvars trustmil trustdiplomat
{txt}
{com}.         foreach t of local trustvars {c -(}
{txt}  2{com}.                 replace trustofficial=1 if `t'==1
{txt}  3{com}.                 replace trustofficial=2 if `t'==2
{txt}  4{com}.                 replace trustofficial=3 if `t'==3
{txt}  5{com}.                 replace trustofficial=4 if `t'==4
{txt}  6{com}.                 {c )-}
{txt}(12 real changes made)
(50 real changes made)
(145 real changes made)
(53 real changes made)
(44 real changes made)
(85 real changes made)
(112 real changes made)
(21 real changes made)

{com}.         tab trustofficial

{txt}trustoffici {c |}
         al {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         56       10.73       10.73
{txt}          2 {c |}{res}        135       25.86       36.59
{txt}          3 {c |}{res}        257       49.23       85.82
{txt}          4 {c |}{res}         74       14.18      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
.         *Binary
.         gen trustofficialbi=.
{txt}(522 missing values generated)

{com}.                 replace trustofficialbi=0 if trustofficial==1|trustofficial==2
{txt}(191 real changes made)

{com}.                 replace trustofficialbi=1 if trustofficial==3|trustofficial==4
{txt}(331 real changes made)

{com}.         tab trustofficialbi

{txt}trustoffici {c |}
       albi {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        191       36.59       36.59
{txt}          1 {c |}{res}        331       63.41      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
. *Treatment Indicators
.         tab handledtreat

     {txt}handledtreat {c |}      Freq.     Percent        Cum.
{hline 18}{c +}{hline 35}
correctly handled {c |}{res}        263       50.38       50.38
{txt}       mishandled {c |}{res}        259       49.62      100.00
{txt}{hline 18}{c +}{hline 35}
            Total {c |}{res}        522      100.00
{txt}
{com}.         gen handled=0
{txt}
{com}.                 replace handled=1 if handledtreat=="correctly handled"
{txt}(263 real changes made)

{com}.         tab handled

    {txt}handled {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        259       49.62       49.62
{txt}          1 {c |}{res}        263       50.38      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
.         gen mishandled=0
{txt}
{com}.                 replace mishandled=1 if handledtreat=="mishandled"
{txt}(259 real changes made)

{com}.         tab mishandled

 {txt}mishandled {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        263       50.38       50.38
{txt}          1 {c |}{res}        259       49.62      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
.         gen military=0
{txt}
{com}.                 replace military=1 if fire_mil==1|fire_mil==2|fire_mil==3|fire_mil==4
{txt}(260 real changes made)

{com}.         tab military

   {txt}military {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        262       50.19       50.19
{txt}          1 {c |}{res}        260       49.81      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
.         gen diplomat=0
{txt}
{com}.                 replace diplomat=1 if fire_fso==1|fire_fso==2|fire_fso==3|fire_fso==4
{txt}(262 real changes made)

{com}.         tab diplomat

   {txt}diplomat {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        260       49.81       49.81
{txt}          1 {c |}{res}        262       50.19      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. *Pre-treatment confidence in institutions
.         *Index
.         gen conindex = (pretrust_1 + pretrust_2 + pretrust_3 + pretrust_4 + pretrust_5 + /// 
>         pretrust_6 + pretrust_7)
{txt}
{com}.         tab conindex

   {txt}conindex {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          7 {c |}{res}          4        0.77        0.77
{txt}          8 {c |}{res}          1        0.19        0.96
{txt}          9 {c |}{res}          2        0.38        1.34
{txt}         10 {c |}{res}          3        0.57        1.92
{txt}         11 {c |}{res}          5        0.96        2.87
{txt}         12 {c |}{res}          4        0.77        3.64
{txt}         13 {c |}{res}         13        2.49        6.13
{txt}         14 {c |}{res}         17        3.26        9.39
{txt}         15 {c |}{res}         15        2.87       12.26
{txt}         16 {c |}{res}         18        3.45       15.71
{txt}         17 {c |}{res}         24        4.60       20.31
{txt}         18 {c |}{res}         34        6.51       26.82
{txt}         19 {c |}{res}         32        6.13       32.95
{txt}         20 {c |}{res}         40        7.66       40.61
{txt}         21 {c |}{res}         52        9.96       50.57
{txt}         22 {c |}{res}         39        7.47       58.05
{txt}         23 {c |}{res}         50        9.58       67.62
{txt}         24 {c |}{res}         38        7.28       74.90
{txt}         25 {c |}{res}         28        5.36       80.27
{txt}         26 {c |}{res}         24        4.60       84.87
{txt}         27 {c |}{res}         26        4.98       89.85
{txt}         28 {c |}{res}         20        3.83       93.68
{txt}         29 {c |}{res}         14        2.68       96.36
{txt}         30 {c |}{res}          8        1.53       97.89
{txt}         31 {c |}{res}          3        0.57       98.47
{txt}         32 {c |}{res}          4        0.77       99.23
{txt}         33 {c |}{res}          1        0.19       99.43
{txt}         35 {c |}{res}          3        0.57      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
.         *Index Quartiles
.         xtile conquart=conindex, n(4)
{txt}
{com}.         tab conquart

{txt}4 quantiles {c |}
of conindex {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        140       26.82       26.82
{txt}          2 {c |}{res}        124       23.75       50.57
{txt}          3 {c |}{res}        155       29.69       80.27
{txt}          4 {c |}{res}        103       19.73      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
.         *High prior confidence dummy
.         gen highconfidence=.
{txt}(522 missing values generated)

{com}.                 replace highconfidence=0 if conquart==1|conquart==2|conquart==3
{txt}(419 real changes made)

{com}.                 replace highconfidence=1 if conquart==4
{txt}(103 real changes made)

{com}.         tab highconfidence

{txt}highconfide {c |}
        nce {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        419       80.27       80.27
{txt}          1 {c |}{res}        103       19.73      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
.         *Low prior confidence dummy
.         gen lowconfidence=.
{txt}(522 missing values generated)

{com}.                 replace lowconfidence=0 if conquart==2|conquart==3|conquart==4
{txt}(382 real changes made)

{com}.                 replace lowconfidence=1 if conquart==1
{txt}(140 real changes made)

{com}.         tab lowconfidence

{txt}lowconfiden {c |}
         ce {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        382       73.18       73.18
{txt}          1 {c |}{res}        140       26.82      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
.         *Pre-treatment confidence in military
.                 *Scale
.                 tab pretrust_1

 {txt}pretrust_1 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         17        3.26        3.26
{txt}          2 {c |}{res}         42        8.05       11.30
{txt}          3 {c |}{res}        124       23.75       35.06
{txt}          4 {c |}{res}        201       38.51       73.56
{txt}          5 {c |}{res}        138       26.44      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
.                 *Binary
.                 gen pre_militarybi=.
{txt}(522 missing values generated)

{com}.                         replace pre_militarybi=0 if pretrust_1==1|pretrust_1==2
{txt}(59 real changes made)

{com}.                         replace pre_militarybi=1 if pretrust_1==3|pretrust_1==4|pretrust_1==5
{txt}(463 real changes made)

{com}.                 tab pre_militarybi 

{txt}pre_militar {c |}
        ybi {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}         59       11.30       11.30
{txt}          1 {c |}{res}        463       88.70      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         
.         *Pre-treatment confidence in diplomats
.                 *Scale
.                 tab pretrust_7

 {txt}pretrust_7 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         63       12.07       12.07
{txt}          2 {c |}{res}        135       25.86       37.93
{txt}          3 {c |}{res}        224       42.91       80.84
{txt}          4 {c |}{res}         85       16.28       97.13
{txt}          5 {c |}{res}         15        2.87      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.                 
.                 *Binary
.                 gen pre_diplomatbi=.
{txt}(522 missing values generated)

{com}.                         replace pre_diplomatbi=0 if pretrust_7==1|pretrust_7==2
{txt}(198 real changes made)

{com}.                         replace pre_diplomatbi=1 if pretrust_7==3|pretrust_7==4|pretrust_7==5
{txt}(324 real changes made)

{com}.                 tab pre_diplomatbi 

{txt}pre_diploma {c |}
        tbi {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        198       37.93       37.93
{txt}          1 {c |}{res}        324       62.07      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.                 
. ***Demographics
. *partisanship
. tab prespartisan

{txt}prespartisa {c |}
          n {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
   Democrat {c |}{res}        259       49.62       49.62
{txt} Republican {c |}{res}        263       50.38      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. gen presdem=.
{txt}(522 missing values generated)

{com}.         replace presdem=0 if prespartisan=="Republican"
{txt}(263 real changes made)

{com}.         replace presdem=1 if prespartisan=="Democrat"
{txt}(259 real changes made)

{com}. tab presdem

    {txt}presdem {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        263       50.38       50.38
{txt}          1 {c |}{res}        259       49.62      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. gen presrep=.
{txt}(522 missing values generated)

{com}.         replace presrep=0 if prespartisan=="Democrat"
{txt}(259 real changes made)

{com}.         replace presrep=1 if prespartisan=="Republican"
{txt}(263 real changes made)

{com}. tab presrep

    {txt}presrep {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        259       49.62       49.62
{txt}          1 {c |}{res}        263       50.38      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. tab pid3

       {txt}pid3 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        192       36.78       36.78
{txt}          2 {c |}{res}        172       32.95       69.73
{txt}          3 {c |}{res}        137       26.25       95.98
{txt}          4 {c |}{res}         21        4.02      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         tab piddem

     {txt}piddem {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        108       62.79       62.79
{txt}          2 {c |}{res}         64       37.21      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        172      100.00
{txt}
{com}.         tab pidrep

     {txt}pidrep {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        108       56.25       56.25
{txt}          2 {c |}{res}         84       43.75      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        192      100.00
{txt}
{com}.         tab pidlean

    {txt}pidlean {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         43       27.22       27.22
{txt}          2 {c |}{res}         49       31.01       58.23
{txt}          3 {c |}{res}         66       41.77      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        158      100.00
{txt}
{com}. 
.         gen republican=.
{txt}(522 missing values generated)

{com}.                 replace republican=1 if pid3==1|pidlean==2
{txt}(241 real changes made)

{com}.                 replace republican=0 if pid3==2|pidlean==1|pidlean==3
{txt}(281 real changes made)

{com}.         tab republican //46%

 {txt}republican {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        281       53.83       53.83
{txt}          1 {c |}{res}        241       46.17      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
.         gen democrat=.
{txt}(522 missing values generated)

{com}.                 replace democrat=1 if pid3==2|pidlean==1
{txt}(215 real changes made)

{com}.                 replace democrat=0 if pid3==1|pidlean==2|pidlean==3
{txt}(307 real changes made)

{com}.         tab democrat //41%

   {txt}democrat {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        307       58.81       58.81
{txt}          1 {c |}{res}        215       41.19      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
.         gen independent=.
{txt}(522 missing values generated)

{com}.                 replace independent=1 if pidlean==3
{txt}(66 real changes made)

{com}.                 replace independent=0 if pid3==1|pid3==2|pidlean==1|pidlean==2
{txt}(456 real changes made)

{com}.         tab independent //13%

{txt}independent {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        456       87.36       87.36
{txt}          1 {c |}{res}         66       12.64      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. gen copartisan=0
{txt}
{com}.         replace copartisan=1 if presrep==1&republican==1
{txt}(125 real changes made)

{com}.         replace copartisan=1 if presdem==1&democrat==1
{txt}(111 real changes made)

{com}. tab copartisan

 {txt}copartisan {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        286       54.79       54.79
{txt}          1 {c |}{res}        236       45.21      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. *Additional Demographics
. tab gender

     {txt}gender {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        302       57.85       57.85
{txt}          2 {c |}{res}        217       41.57       99.43
{txt}          3 {c |}{res}          2        0.38       99.81
{txt}          4 {c |}{res}          1        0.19      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. gen male=.
{txt}(522 missing values generated)

{com}.         replace male=1 if gender==2
{txt}(217 real changes made)

{com}.         replace male=0 if gender==1|gender==3|gender==4
{txt}(305 real changes made)

{com}. tab male

       {txt}male {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        305       58.43       58.43
{txt}          1 {c |}{res}        217       41.57      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. tab race

       {txt}race {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        437       83.72       83.72
{txt}        1,2 {c |}{res}          3        0.57       84.29
{txt}    1,2,3,5 {c |}{res}          1        0.19       84.48
{txt}        1,3 {c |}{res}          1        0.19       84.67
{txt}          2 {c |}{res}         52        9.96       94.64
{txt}        2,3 {c |}{res}          2        0.38       95.02
{txt}          3 {c |}{res}          6        1.15       96.17
{txt}          4 {c |}{res}         14        2.68       98.85
{txt}          5 {c |}{res}          6        1.15      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. gen white=0
{txt}
{com}.         replace white=1 if race=="1"|race=="1,2"|race=="1,2,3,5"|race=="1,3"
{txt}(442 real changes made)

{com}. tab white

      {txt}white {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}         80       15.33       15.33
{txt}          1 {c |}{res}        442       84.67      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. tab education

  {txt}education {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         12        2.30        2.30
{txt}          2 {c |}{res}        121       23.18       25.48
{txt}          3 {c |}{res}        119       22.80       48.28
{txt}          4 {c |}{res}         69       13.22       61.49
{txt}          5 {c |}{res}        144       27.59       89.08
{txt}          6 {c |}{res}         57       10.92      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. gen college=.
{txt}(522 missing values generated)

{com}.         replace college=0 if education==1|education==2|education==3|education==4
{txt}(321 real changes made)

{com}.         replace college=1 if education==5|education==6
{txt}(201 real changes made)

{com}. tab college

    {txt}college {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        321       61.49       61.49
{txt}          1 {c |}{res}        201       38.51      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. *Post-treatment attention to current events
. tab currentevents_1

{txt}currenteven {c |}
       ts_1 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         62       11.88       11.88
{txt}          2 {c |}{res}        150       28.74       40.61
{txt}          3 {c |}{res}        223       42.72       83.33
{txt}          4 {c |}{res}         87       16.67      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         rename currentevents_1 primaries
{res}{txt}
{com}. tab primaries

{txt}currenteven {c |}
       ts_1 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         62       11.88       11.88
{txt}          2 {c |}{res}        150       28.74       40.61
{txt}          3 {c |}{res}        223       42.72       83.33
{txt}          4 {c |}{res}         87       16.67      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. tab currentevents_2

{txt}currenteven {c |}
       ts_2 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         78       14.94       14.94
{txt}          2 {c |}{res}        183       35.06       50.00
{txt}          3 {c |}{res}        187       35.82       85.82
{txt}          4 {c |}{res}         74       14.18      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         rename currentevents_2 biden
{res}{txt}
{com}. tab biden

{txt}currenteven {c |}
       ts_2 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         78       14.94       14.94
{txt}          2 {c |}{res}        183       35.06       50.00
{txt}          3 {c |}{res}        187       35.82       85.82
{txt}          4 {c |}{res}         74       14.18      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. tab currentevents_3

{txt}currenteven {c |}
       ts_3 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         45        8.62        8.62
{txt}          2 {c |}{res}        142       27.20       35.82
{txt}          3 {c |}{res}        197       37.74       73.56
{txt}          4 {c |}{res}        138       26.44      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}.         rename currentevents_3 trump
{res}{txt}
{com}. tab trump

{txt}currenteven {c |}
       ts_3 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}         45        8.62        8.62
{txt}          2 {c |}{res}        142       27.20       35.82
{txt}          3 {c |}{res}        197       37.74       73.56
{txt}          4 {c |}{res}        138       26.44      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. *Create attention index
. gen currentindex = (primaries + biden + trump)
{txt}
{com}. tab currentindex

{txt}currentinde {c |}
          x {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          3 {c |}{res}         24        4.60        4.60
{txt}          4 {c |}{res}         20        3.83        8.43
{txt}          5 {c |}{res}         28        5.36       13.79
{txt}          6 {c |}{res}         76       14.56       28.35
{txt}          7 {c |}{res}         75       14.37       42.72
{txt}          8 {c |}{res}         70       13.41       56.13
{txt}          9 {c |}{res}        103       19.73       75.86
{txt}         10 {c |}{res}         42        8.05       83.91
{txt}         11 {c |}{res}         36        6.90       90.80
{txt}         12 {c |}{res}         48        9.20      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. *Index quartiles
. xtile currentquart=currentindex, n(4)
{txt}
{com}.         tab currentquart

{txt}4 quantiles {c |}
         of {c |}
currentinde {c |}
          x {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        148       28.35       28.35
{txt}          2 {c |}{res}        145       27.78       56.13
{txt}          3 {c |}{res}        103       19.73       75.86
{txt}          4 {c |}{res}        126       24.14      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. *Dummy for high attention based on quartiles
. gen highnews=.
{txt}(522 missing values generated)

{com}.         replace highnews=0 if currentquart==1|currentquart==2|currentquart==3
{txt}(396 real changes made)

{com}.         replace highnews=1 if currentquart==4
{txt}(126 real changes made)

{com}. tab highnews

   {txt}highnews {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}        396       75.86       75.86
{txt}          1 {c |}{res}        126       24.14      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        522      100.00
{txt}
{com}. 
. *Use manipulation check to assess data quality
. tab manip_handling mishandled, column
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

manip_hand {c |}      mishandled
      ling {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         1 {c |}{res}        47        238 {txt}{c |}{res}       285 
           {txt}{c |}{res}     18.01      91.89 {txt}{c |}{res}     54.81 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         2 {c |}{res}       214         21 {txt}{c |}{res}       235 
           {txt}{c |}{res}     81.99       8.11 {txt}{c |}{res}     45.19 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       261        259 {txt}{c |}{res}       520 
           {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 
{txt}
{com}. 
. ********************************************************************************
. *Analysis reported in the main text
. 
. *Stage one comparisons of proportions by treatment condition
.         *Confidence in institutions
.         prtest institutionsbi, by(handled) 

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     259
                                                   1{txt}: Number of obs = {res}     263
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .5405405{col 28} .0309662{col 58} .4798479{col 70} .6012332
           {txt}1 {c |}{res}{col 17} .6920152{col 28} .0284672{col 58} .6362205{col 70} .7478099
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.1514747{col 28} .0420629{col 58}-.2339164{col 70}-.0690329
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0425579{col 38}   -3.56{col 49}0.000
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -3.5593
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0002         {txt}Pr(|Z| > |z|) = {res}0.0004          {txt}Pr(Z > z) = {res}0.9998
{txt}
{com}.         *Trust in president
.         prtest trustpresbi, by(handled) 

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     259
                                                   1{txt}: Number of obs = {res}     263
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .5019305{col 28} .0310683{col 58} .4410378{col 70} .5628232
           {txt}1 {c |}{res}{col 17} .6235741{col 28} .0298749{col 58} .5650205{col 70} .6821278
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.1216436{col 28} .0431016{col 58}-.2061211{col 70}-.0371661
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0434188{col 38}   -2.80{col 49}0.005
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -2.8016
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0025         {txt}Pr(|Z| > |z|) = {res}0.0051          {txt}Pr(Z > z) = {res}0.9975
{txt}
{com}.         *Trust in Congress
.         prtest trustcongressbi, by(handled)

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     259
                                                   1{txt}: Number of obs = {res}     263
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .4864865{col 28} .0310571{col 58} .4256156{col 70} .5473574
           {txt}1 {c |}{res}{col 17} .5627376{col 28} .0305877{col 58} .5027869{col 70} .6226883
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0762512{col 28} .0435907{col 58}-.1616874{col 70} .0091851
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0437158{col 38}   -1.74{col 49}0.081
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -1.7442
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0406         {txt}Pr(|Z| > |z|) = {res}0.0811          {txt}Pr(Z > z) = {res}0.9594
{txt}
{com}. 
. *Figure 3. Public Confidence and Trust by Treatment Condition
. mean institutionsbi if handled==1
{res}
{txt}{col 1}Mean estimation{col 46}{lalign 13:Number of obs}{col 59} = {res}{ralign 3:263}

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 16}{c |}       Mean{col 28}   Std. err.{col 40}     [95% con{col 53}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
institutionsbi {c |}{col 16}{res}{space 2} .6920152{col 28}{space 2} .0285215{col 39}{space 5} .6358547{col 53}{space 3} .7481757
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store correct
{txt}
{com}. mean institutionsbi if handled==0
{res}
{txt}{col 1}Mean estimation{col 46}{lalign 13:Number of obs}{col 59} = {res}{ralign 3:259}

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 16}{c |}       Mean{col 28}   Std. err.{col 40}     [95% con{col 53}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
institutionsbi {c |}{col 16}{res}{space 2} .5405405{col 28}{space 2} .0310261{col 39}{space 5} .4794438{col 53}{space 3} .6016373
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store incorrect
{txt}
{com}. 
. coefplot correct incorrect, /// 
>         vertical ciopts(recast(rcap)) xlabel(none) ylabel(0(0.2)1) /// 
>         ytitle("Proportion Confident") title("Democratic Institutions") /// 
>         scheme(s1mono) name(democracy)
{res}{txt}
{com}. 
. mean trustpresbi if handled==1
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:263}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 1}trustpresbi {c |}{col 14}{res}{space 2} .6235741{col 26}{space 2} .0299318{col 37}{space 5} .5646366{col 51}{space 3} .6825117
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store correct
{txt}
{com}. mean trustpresbi if handled==0
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:259}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 1}trustpresbi {c |}{col 14}{res}{space 2} .5019305{col 26}{space 2} .0311284{col 37}{space 5} .4406324{col 51}{space 3} .5632286
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store incorrect
{txt}
{com}. 
. coefplot correct incorrect, /// 
>         vertical ciopts(recast(rcap)) xlabel(none) ylabel(0(0.2)1) /// 
>         ytitle("Proportion Trust") title("President") /// 
>         scheme(s1mono) name(presidency)
{res}{txt}
{com}. 
. mean trustcongressbi if handled==1
{res}
{txt}{col 1}Mean estimation{col 47}{lalign 13:Number of obs}{col 60} = {res}{ralign 3:263}

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 17}{c |}       Mean{col 29}   Std. err.{col 41}     [95% con{col 54}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
trustcongressbi {c |}{col 17}{res}{space 2} .5627376{col 29}{space 2}  .030646{col 40}{space 5} .5023939{col 54}{space 3} .6230814
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store correct
{txt}
{com}. mean trustcongressbi if handled==0
{res}
{txt}{col 1}Mean estimation{col 47}{lalign 13:Number of obs}{col 60} = {res}{ralign 3:259}

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 17}{c |}       Mean{col 29}   Std. err.{col 41}     [95% con{col 54}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
trustcongressbi {c |}{col 17}{res}{space 2} .4864865{col 29}{space 2} .0311173{col 40}{space 5} .4252103{col 54}{space 3} .5477627
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store incorrect
{txt}
{com}. 
. coefplot correct incorrect, /// 
>         vertical ciopts(recast(rcap)) xlabel(none) ylabel(0(0.2)1) /// 
>         ytitle("Proportion Trust") title("Congress") /// 
>         scheme(s1mono) name(congressional)
{res}{txt}
{com}. 
. graph combine democracy presidency congressional, /// 
>         altshrink ycommon rows(1) iscale(1.5) scheme(s1mono) /// 
>         note("The figure compares the proportions of post-treatment confidence in democratic institutions, trust in the" /// 
>         "president, and trust in Congress, respectively, by treatment condition with 95% confidence intervals. The" /// 
>         "figure uses binary measures of each variable, 4-point measures are reported in the appendix.", span)
{res}{txt}
{com}. 
. *Exploratory Partisanship Analysis
.         *Party ID
.         *Differences in confidence between partisan subgroups
.         prtest institutionsbi if democrat==1|republican==1, by(republican) 

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     215
                                                   1{txt}: Number of obs = {res}     241
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17}  .744186{col 28} .0297566{col 58} .6858641{col 70}  .802508
           {txt}1 {c |}{res}{col 17}  .526971{col 28} .0321609{col 58} .4639367{col 70} .5900052
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .2172151{col 28} .0438153{col 58} .1313386{col 70} .3030915
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0453079{col 38}    4.79{col 49}0.000
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res}  4.7942
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}1.0000         {txt}Pr(|Z| > |z|) = {res}0.0000          {txt}Pr(Z > z) = {res}0.0000
{txt}
{com}.         prtest institutionsbi if democrat==1|independent==1, by(independent) 

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     215
                                                   1{txt}: Number of obs = {res}      66
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17}  .744186{col 28} .0297566{col 58} .6858641{col 70}  .802508
           {txt}1 {c |}{res}{col 17}  .530303{col 28} .0614326{col 58} .4098973{col 70} .6507087
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}  .213883{col 28}   .06826{col 58}  .080096{col 70} .3476701
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0648518{col 38}    3.30{col 49}0.001
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res}  3.2980
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.9995         {txt}Pr(|Z| > |z|) = {res}0.0010          {txt}Pr(Z > z) = {res}0.0005
{txt}
{com}.         prtest institutionsbi if republican==1|independent==1, by(republican) 

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}      66
                                                   1{txt}: Number of obs = {res}     241
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17}  .530303{col 28} .0614326{col 58} .4098973{col 70} .6507087
           {txt}1 {c |}{res}{col 17}  .526971{col 28} .0321609{col 58} .4639367{col 70} .5900052
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0033321{col 28} .0693418{col 58}-.1325754{col 70} .1392396
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0693572{col 38}    0.05{col 49}0.962
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res}  0.0480
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.5192         {txt}Pr(|Z| > |z|) = {res}0.9617          {txt}Pr(Z > z) = {res}0.4808
{txt}
{com}.         
.         *Confidence by treatment within each partisan subgroup
.         prtest institutionsbi if democrat==1, by(handled)

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     102
                                                   1{txt}: Number of obs = {res}     113
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .6764706{col 28} .0463214{col 58} .5856824{col 70} .7672588
           {txt}1 {c |}{res}{col 17} .8053097{col 28}  .037249{col 58} .7323031{col 70} .8783164
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.1288391{col 28} .0594403{col 58}-.2453401{col 70}-.0123382
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0595913{col 38}   -2.16{col 49}0.031
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -2.1620
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0153         {txt}Pr(|Z| > |z|) = {res}0.0306          {txt}Pr(Z > z) = {res}0.9847
{txt}
{com}.         prtest institutionsbi if republican==1, by(handled)

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     123
                                                   1{txt}: Number of obs = {res}     118
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .4471545{col 28}  .044831{col 58} .3592874{col 70} .5350216
           {txt}1 {c |}{res}{col 17} .6101695{col 28} .0448975{col 58}  .522172{col 70}  .698167
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} -.163015{col 28} .0634476{col 58}-.2873701{col 70}  -.03866
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0643357{col 38}   -2.53{col 49}0.011
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -2.5338
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0056         {txt}Pr(|Z| > |z|) = {res}0.0113          {txt}Pr(Z > z) = {res}0.9944
{txt}
{com}.         prtest institutionsbi if independent==1, by(handled) 

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}      34
                                                   1{txt}: Number of obs = {res}      32
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .4705882{col 28} .0856008{col 58} .3028137{col 70} .6383627
           {txt}1 {c |}{res}{col 17}   .59375{col 28} .0868207{col 58} .4235845{col 70} .7639155
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.1231618{col 28} .1219235{col 58}-.3621274{col 70} .1158039
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .1229217{col 38}   -1.00{col 49}0.316
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -1.0020
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.1582         {txt}Pr(|Z| > |z|) = {res}0.3164          {txt}Pr(Z > z) = {res}0.8418
{txt}
{com}.         
.         *Copartisanship
.         *Differences in confidence between copartisan and non subgroups
.         prtest institutionsbi, by(copartisan)

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     286
                                                   1{txt}: Number of obs = {res}     236
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .5769231{col 28} .0292136{col 58} .5196654{col 70} .6341808
           {txt}1 {c |}{res}{col 17} .6652542{col 28} .0307182{col 58} .6050477{col 70} .7254607
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0883312{col 28} .0423915{col 58}-.1714171{col 70}-.0052453
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0427532{col 38}   -2.07{col 49}0.039
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -2.0661
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0194         {txt}Pr(|Z| > |z|) = {res}0.0388          {txt}Pr(Z > z) = {res}0.9806
{txt}
{com}.         
.         *Confidence by treatment within each copartisan subgroup
.         prtest institutionsbi if copartisan==1, by(handled)

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     116
                                                   1{txt}: Number of obs = {res}     120
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .5862069{col 28} .0457286{col 58} .4965804{col 70} .6758333
           {txt}1 {c |}{res}{col 17} .7416667{col 28}  .039958{col 58} .6633504{col 70}  .819983
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.1554598{col 28} .0607268{col 58}-.2744822{col 70}-.0364373
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0614452{col 38}   -2.53{col 49}0.011
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -2.5301
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0057         {txt}Pr(|Z| > |z|) = {res}0.0114          {txt}Pr(Z > z) = {res}0.9943
{txt}
{com}.         prtest institutionsbi if copartisan==0, by(handled)

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     143
                                                   1{txt}: Number of obs = {res}     143
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .5034965{col 28} .0418111{col 58} .4215483{col 70} .5854447
           {txt}1 {c |}{res}{col 17} .6503497{col 28}  .039877{col 58} .5721922{col 70} .7285071
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.1468531{col 28} .0577784{col 58}-.2600967{col 70}-.0336096
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0584273{col 38}   -2.51{col 49}0.012
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -2.5134
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0060         {txt}Pr(|Z| > |z|) = {res}0.0120          {txt}Pr(Z > z) = {res}0.9940
{txt}
{com}.         
.         *Figure 4. Partisan Subgroup Analysis
.         *means by respondent party id
.         mean institutionsbi if democrat==1
{res}
{txt}{col 1}Mean estimation{col 46}{lalign 13:Number of obs}{col 59} = {res}{ralign 3:215}

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 16}{c |}       Mean{col 28}   Std. err.{col 40}     [95% con{col 53}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
institutionsbi {c |}{col 16}{res}{space 2}  .744186{col 28}{space 2} .0298261{col 39}{space 5} .6853956{col 53}{space 3} .8029765
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store Democrats
{txt}
{com}.         mean institutionsbi if republican==1
{res}
{txt}{col 1}Mean estimation{col 46}{lalign 13:Number of obs}{col 59} = {res}{ralign 3:241}

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 16}{c |}       Mean{col 28}   Std. err.{col 40}     [95% con{col 53}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
institutionsbi {c |}{col 16}{res}{space 2}  .526971{col 28}{space 2} .0322279{col 39}{space 5} .4634853{col 53}{space 3} .5904566
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store Republicans 
{txt}
{com}.         mean institutionsbi if independent==1
{res}
{txt}{col 1}Mean estimation{col 47}{lalign 13:Number of obs}{col 60} = {res}{ralign 2:66}

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 16}{c |}       Mean{col 28}   Std. err.{col 40}     [95% con{col 53}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
institutionsbi {c |}{col 16}{res}{space 2}  .530303{col 28}{space 2} .0619034{col 39}{space 5} .4066735{col 53}{space 3} .6539326
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store Independents
{txt}
{com}.         
.         coefplot Democrats Republicans Independents, /// 
>                 vertical ciopts(recast(rcap)) ylabel(0(0.2)1) xlabel(none) legend(rows(1)) /// 
>                 ytitle("Proportion Confident") title("Confidence by Party ID") /// 
>                 scheme(s1mono) name(pidmean)
{res}{txt}
{com}.         
.         *treatment effects by respondent party id
.         reg institutionsbi mishandled if democrat==1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       215
{txt}{hline 13}{c +}{hline 34}   F(1, 213)       = {res}     4.73
{txt}       Model {c |} {res} .889888987         1  .889888987   {txt}Prob > F        ={res}    0.0307
{txt}    Residual {c |} {res} 40.0403436       213  .187982834   {txt}R-squared       ={res}    0.0217
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0171
{txt}       Total {c |} {res} 40.9302326       214  .191262769   {txt}Root MSE        =   {res} .43357

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}institutio~i{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}mishandled {c |}{col 14}{res}{space 2}-.1288391{col 26}{space 2}  .059216{col 37}{space 1}   -2.18{col 46}{space 3}0.031{col 54}{space 4}-.2455636{col 67}{space 3}-.0121147
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .8053097{col 26}{space 2} .0407868{col 37}{space 1}   19.74{col 46}{space 3}0.000{col 54}{space 4} .7249122{col 67}{space 3} .8857072
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 est store Democrats
{txt}
{com}.         reg institutionsbi mishandled if republican==1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       241
{txt}{hline 13}{c +}{hline 34}   F(1, 239)       = {res}     6.54
{txt}       Model {c |} {res} 1.60038812         1  1.60038812   {txt}Prob > F        ={res}    0.0112
{txt}    Residual {c |} {res} 58.4743007       239  .244662346   {txt}R-squared       ={res}    0.0266
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0226
{txt}       Total {c |} {res} 60.0746888       240  .250311203   {txt}Root MSE        =   {res} .49463

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}institutio~i{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}mishandled {c |}{col 14}{res}{space 2} -.163015{col 26}{space 2}  .063738{col 37}{space 1}   -2.56{col 46}{space 3}0.011{col 54}{space 4} -.288575{col 67}{space 3} -.037455
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6101695{col 26}{space 2} .0455347{col 37}{space 1}   13.40{col 46}{space 3}0.000{col 54}{space 4} .5204689{col 67}{space 3} .6998701
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 est store Republicans
{txt}
{com}.         reg institutionsbi mishandled if independent==1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}        66
{txt}{hline 13}{c +}{hline 34}   F(1, 64)        = {res}     0.99
{txt}       Model {c |} {res} .250055704         1  .250055704   {txt}Prob > F        ={res}    0.3238
{txt}    Residual {c |} {res} 16.1893382        64   .25295841   {txt}R-squared       ={res}    0.0152
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0002
{txt}       Total {c |} {res} 16.4393939        65  .252913753   {txt}Root MSE        =   {res} .50295

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}institutio~i{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}mishandled {c |}{col 14}{res}{space 2}-.1231618{col 26}{space 2} .1238745{col 37}{space 1}   -0.99{col 46}{space 3}0.324{col 54}{space 4}-.3706296{col 67}{space 3} .1243061
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}   .59375{col 26}{space 2} .0889098{col 37}{space 1}    6.68{col 46}{space 3}0.000{col 54}{space 4} .4161323{col 67}{space 3} .7713677
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 est store Independents
{txt}
{com}.         
.         coefplot Democrats Republicans Independents, keep(mishandled) /// 
>                 xline(0) xlabel(-0.4(0.1)0.1) xtitle("Change from Correctly Handled") /// 
>                 ylabel(none) legend(rows(1)) /// 
>                 title("Treatment Effect By Party ID") scheme(s1mono) name(pideffect)
{res}{txt}
{com}.         
.         *means by copartisanship with president
.         mean institutionsbi if copartisan==1
{res}
{txt}{col 1}Mean estimation{col 46}{lalign 13:Number of obs}{col 59} = {res}{ralign 3:236}

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 16}{c |}       Mean{col 28}   Std. err.{col 40}     [95% con{col 53}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
institutionsbi {c |}{col 16}{res}{space 2} .6652542{col 28}{space 2} .0307835{col 39}{space 5} .6046074{col 53}{space 3}  .725901
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store copartisan
{txt}
{com}.         mean institutionsbi if copartisan==0
{res}
{txt}{col 1}Mean estimation{col 46}{lalign 13:Number of obs}{col 59} = {res}{ralign 3:286}

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 16}{c |}       Mean{col 28}   Std. err.{col 40}     [95% con{col 53}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
institutionsbi {c |}{col 16}{res}{space 2} .5769231{col 28}{space 2} .0292648{col 39}{space 5} .5193204{col 53}{space 3} .6345257
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store noncopartisan 
{txt}
{com}.         
.         coefplot copartisan noncopartisan, /// 
>                 vertical ciopts(recast(rcap)) ylabel(0(0.2)1) xlabel(none) legend(rows(1)) /// 
>                 ytitle("Proportion Confident") title("Confidence by Copartisanship") /// 
>                 scheme(s1mono) name(copartmean)
{res}{txt}
{com}.         
.         *treatment effects by copartisanship
.         reg institutionsbi mishandled if copartisan==1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       236
{txt}{hline 13}{c +}{hline 34}   F(1, 234)       = {res}     6.52
{txt}       Model {c |} {res} 1.42548704         1  1.42548704   {txt}Prob > F        ={res}    0.0113
{txt}    Residual {c |} {res} 51.1295977       234  .218502554   {txt}R-squared       ={res}    0.0271
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0230
{txt}       Total {c |} {res} 52.5550847       235  .223638658   {txt}Root MSE        =   {res} .46744

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}institutio~i{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}mishandled {c |}{col 14}{res}{space 2}-.1554598{col 26}{space 2} .0608646{col 37}{space 1}   -2.55{col 46}{space 3}0.011{col 54}{space 4}-.2753723{col 67}{space 3}-.0355472
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .7416667{col 26}{space 2} .0426715{col 37}{space 1}   17.38{col 46}{space 3}0.000{col 54}{space 4} .6575973{col 67}{space 3}  .825736
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 est store copartisan
{txt}
{com}.         reg institutionsbi mishandled if copartisan==0

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       286
{txt}{hline 13}{c +}{hline 34}   F(1, 284)       = {res}     6.41
{txt}       Model {c |} {res} 1.54195804         1  1.54195804   {txt}Prob > F        ={res}    0.0119
{txt}    Residual {c |} {res} 68.2657343       284  .240372304   {txt}R-squared       ={res}    0.0221
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0186
{txt}       Total {c |} {res} 69.8076923       285  .244939271   {txt}Root MSE        =   {res} .49028

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}institutio~i{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}mishandled {c |}{col 14}{res}{space 2}-.1468531{col 26}{space 2} .0579815{col 37}{space 1}   -2.53{col 46}{space 3}0.012{col 54}{space 4}-.2609811{col 67}{space 3}-.0327252
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6503497{col 26}{space 2} .0409991{col 37}{space 1}   15.86{col 46}{space 3}0.000{col 54}{space 4}  .569649{col 67}{space 3} .7310503
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 est store noncopartisan 
{txt}
{com}.         
.         coefplot copartisan noncopartisan, keep(mishandled) /// 
>                 xline(0) xlabel(-0.4(0.1)0.1) xtitle("Change from Correctly Handled") /// 
>                 ylabel(none) legend(rows(1)) /// 
>                 title("Treatment Effect by Copartisanship") scheme(s1mono) name(coparteffect)
{res}{txt}
{com}. 
.         graph combine pidmean pideffect copartmean coparteffect, /// 
>                 altshrink iscale(1.45) scheme(s1mono) /// 
>                 note("Figure reports the proportion of respondents confident in democratic institutions (left column) " /// 
>                 "and the effect of the incorrectly handled treatment relative to the correctly handled treatment (right column) " /// 
>                 "for each relevant subgroup, both with 95% confidence intervals. The relevant subgroups are party" /// 
>                 "identifications (top row) and copartisanship or non-copartisanship with the president (bottom row). ")
{res}{txt}
{com}.         
. *Stage two results
.         *Pre-treatment confidence in military vs. diplomats
.         prtest pre_militarybi==pre_diplomatbi

{txt}Two-sample test of proportions          {res}pre_military{txt}: Number of obs = {res}     522
                                        pre_diplomat{txt}: Number of obs = {res}     522
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
pre_military {c |}{res}{col 17} .8869732{col 28} .0138583{col 58} .8598114{col 70}  .914135
{txt}pre_diplomat {c |}{res}{col 17} .6206897{col 28} .0212373{col 58} .5790653{col 70}  .662314
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .2662835{col 28} .0253589{col 58} .2165809{col 70} .3159861
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0266645{col 38}    9.99{col 49}0.000
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}pre_military{txt}) - prop({res}pre_diplomat{txt})            z = {res}  9.9864
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}1.0000         {txt}Pr(|Z| > |z|) = {res}0.0000          {txt}Pr(Z > z) = {res}0.0000
{txt}
{com}.         
.         *Post-treatment trust in miltiary vs. diplomatic officials
.         prtest trustofficialbi, by(military)

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     262
                                                   1{txt}: Number of obs = {res}     260
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .5076336{col 28} .0308865{col 58} .4470972{col 70}   .56817
           {txt}1 {c |}{res}{col 17} .7615385{col 28} .0264283{col 58}   .70974{col 70} .8133369
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.2539049{col 28} .0406501{col 58}-.3335776{col 70}-.1742322
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0421656{col 38}   -6.02{col 49}0.000
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -6.0216
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.0000         {txt}Pr(|Z| > |z|) = {res}0.0000          {txt}Pr(Z > z) = {res}1.0000
{txt}
{com}.         
.         *Post-treatment support for firing military vs. diplomatic officials
.         prtest firebi, by(military)

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     262
                                                   1{txt}: Number of obs = {res}     260
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .7480916{col 28} .0268193{col 58} .6955267{col 70} .8006565
           {txt}1 {c |}{res}{col 17} .7192308{col 28} .0278691{col 58} .6646084{col 70} .7738531
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} .0288608{col 28} .0386777{col 58} -.046946{col 70} .1046676
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0386932{col 38}    0.75{col 49}0.456
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res}  0.7459
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.7721         {txt}Pr(|Z| > |z|) = {res}0.4557          {txt}Pr(Z > z) = {res}0.2279
{txt}
{com}. 
.         *Figure 5. Influence of Military Affiliations
.         *pre-treatment trust
.         mean pre_militarybi
{res}
{txt}{col 1}Mean estimation{col 46}{lalign 13:Number of obs}{col 59} = {res}{ralign 3:522}

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 16}{c |}       Mean{col 28}   Std. err.{col 40}     [95% con{col 53}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
pre_militarybi {c |}{col 16}{res}{space 2} .8869732{col 28}{space 2} .0138716{col 39}{space 5}  .859722{col 53}{space 3} .9142244
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store military
{txt}
{com}.         mean pre_diplomatbi
{res}
{txt}{col 1}Mean estimation{col 46}{lalign 13:Number of obs}{col 59} = {res}{ralign 3:522}

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 16}{c |}       Mean{col 28}   Std. err.{col 40}     [95% con{col 53}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
pre_diplomatbi {c |}{col 16}{res}{space 2} .6206897{col 28}{space 2} .0212577{col 39}{space 5} .5789284{col 53}{space 3} .6624509
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store diplomats
{txt}
{com}. 
.         coefplot military diplomats, vertical xlabel(none) /// 
>                 ytitle("Proportion Confident") ylabel(0(0.2)1) /// 
>                 title("Pre-Treatment" "Confidence") scheme(s1mono) name(pretreat)
{res}{txt}
{com}. 
.         *post-treatment trust
.         mean trustofficialbi if military==1
{res}
{txt}{col 1}Mean estimation{col 47}{lalign 13:Number of obs}{col 60} = {res}{ralign 3:260}

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 17}{c |}       Mean{col 29}   Std. err.{col 41}     [95% con{col 54}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
trustofficialbi {c |}{col 17}{res}{space 2} .7615385{col 29}{space 2} .0264792{col 40}{space 5} .7093965{col 54}{space 3} .8136804
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store military
{txt}
{com}.         mean trustofficialbi if diplomat==1
{res}
{txt}{col 1}Mean estimation{col 47}{lalign 13:Number of obs}{col 60} = {res}{ralign 3:262}

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 17}{c |}       Mean{col 29}   Std. err.{col 41}     [95% con{col 54}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
trustofficialbi {c |}{col 17}{res}{space 2} .5076336{col 29}{space 2} .0309456{col 40}{space 5} .4466987{col 54}{space 3} .5685684
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store diplomats
{txt}
{com}. 
.         coefplot military diplomats, vertical xlabel(none) /// 
>                 ytitle("Proportion Trust") ylabel(0(0.2)1) /// 
>                 title("Trust in""Officials Who Mishandled") /// 
>                 scheme(s1mono) name(post)
{res}{txt}
{com}. 
.         *Support for Firing
.         mean firebi if military==1
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:260}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 6}firebi {c |}{col 14}{res}{space 2} .7192308{col 26}{space 2} .0279228{col 37}{space 5} .6642461{col 51}{space 3} .7742154
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store military
{txt}
{com}.         mean firebi if diplomat==1
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:262}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 6}firebi {c |}{col 14}{res}{space 2} .7480916{col 26}{space 2} .0268707{col 37}{space 5} .6951807{col 51}{space 3} .8010025
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store diplomats
{txt}
{com}.         coefplot military diplomats, vertical xlabel(none) /// 
>                 ytitle("Proportion Support") ylabel(0(0.2)1) /// 
>                 title("Support for Firing""Officials Who Mishandled") /// 
>                 scheme(s1mono) name(fire)
{res}{txt}
{com}.         
.         graph combine pretreat post fire, altshrink ycommon rows(1) /// 
>                 iscale(1.4) scheme(s1mono) /// 
>                 note("Figure reports comparisons of proportion for three measures with 95% confidence intervals." /// 
>                 "The first panel reports the proportions of pre-treatment confidence in the military and in U.S. diplomats." /// 
>                 "The second panel reports the proportions of post-treatment trust in the officials who mishandled documents," /// 
>                 "comparing the military and diplomat treatment conditions. The third panel reports the proportions of" /// 
>                 "post-treatment support for firing the officials who mishandled documents, comparing the military and" /// 
>                 "diplomat treatment conditions. All panels use binary measures of the relevant variable. The appendix" /// 
>                 "reports results using the 4-point measure.")
{res}{txt}
{com}. 
.                 
. ********************************************************************************
. *Analysis included in appendix
. 
. *A5.1 Pre-treatment confidence in institutions
. graph bar pretrust_1-pretrust_7, horizontal legend(label(1 "Military") label(2 "Police") /// 
>         label(3 "Small Business") label(4 "The Presidency") label(5 "Congress") /// 
>         label(6 "Supreme Court") label(7 "Diplomats")) blabel(bar) /// 
>         ytitle("Level of Confidence") scheme(stmono1) /// 
>         note("Figure includes the mean level of pre-treatment confidence in each actor from the main survey." /// 
>         "Confidence was measured on a five-point scale ranging from 1 (none) to 5 (a great deal).", span)
{res}{txt}
{com}. 
. *A5.2 Replication of main analyses using 4-point measures
. *Figure A5.2 Public Confidence and Trust by Treatment COnditoin with 4-Point Measure
. ttest institutions, by(mishandled)

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    263{col 22} 2.775665{col 34} .0530284{col 46} .8599757{col 58} 2.671249{col 70} 2.880081
       {txt}1 {c |}{res}{col 12}    259{col 22} 2.513514{col 34} .0572094{col 46}  .920698{col 58} 2.400857{col 70}  2.62617
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    522{col 22} 2.645594{col 34} .0393651{col 46} .8993865{col 58}  2.56826{col 70} 2.722928
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .2621519{col 34} .0779651{col 58} .1089865{col 70} .4153172
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  3.3624
{txt}H0: diff = 0                                     Degrees of freedom = {res}     520

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.9996         {txt}Pr(|T| > |t|) = {res}0.0008          {txt}Pr(T > t) = {res}0.0004
{txt}
{com}. ttest trustpres, by(mishandled)

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    263{col 22}  2.60076{col 34} .0598812{col 46} .9711091{col 58} 2.482851{col 70}  2.71867
       {txt}1 {c |}{res}{col 12}    259{col 22} 2.447876{col 34} .0594345{col 46} .9565084{col 58} 2.330838{col 70} 2.564915
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    522{col 22} 2.524904{col 34} .0422808{col 46}  .966002{col 58} 2.441842{col 70} 2.607966
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}  .152884{col 34} .0843793{col 58}-.0128823{col 70} .3186503
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  1.8119
{txt}H0: diff = 0                                     Degrees of freedom = {res}     520

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.9647         {txt}Pr(|T| > |t|) = {res}0.0706          {txt}Pr(T > t) = {res}0.0353
{txt}
{com}. ttest trustcongress, by(mishandled)

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    263{col 22} 2.501901{col 34}   .05411{col 46} .8775161{col 58} 2.395355{col 70} 2.608447
       {txt}1 {c |}{res}{col 12}    259{col 22} 2.382239{col 34} .0567439{col 46} .9132069{col 58} 2.270499{col 70}  2.49398
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    522{col 22} 2.442529{col 34} .0392407{col 46} .8965447{col 58} 2.365439{col 70} 2.519618
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .1196618{col 34} .0783837{col 58}-.0343258{col 70} .2736493
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  1.5266
{txt}H0: diff = 0                                     Degrees of freedom = {res}     520

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.9363         {txt}Pr(|T| > |t|) = {res}0.1275          {txt}Pr(T > t) = {res}0.0637
{txt}
{com}. 
. mean institutions if handled==1
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:263}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
institutions {c |}{col 14}{res}{space 2} 2.775665{col 26}{space 2} .0530284{col 37}{space 5} 2.671249{col 51}{space 3} 2.880081
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store correct
{txt}
{com}. mean institutions if handled==0
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:259}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
institutions {c |}{col 14}{res}{space 2} 2.513514{col 26}{space 2} .0572094{col 37}{space 5} 2.400857{col 51}{space 3}  2.62617
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store incorrect
{txt}
{com}. 
. coefplot correct incorrect, /// 
>         vertical ciopts(recast(rcap)) xlabel(none) /// 
>         ytitle("Mean Confident") title("Democratic Institutions") /// 
>         scheme(s1mono) name(democracy4)
{res}{txt}
{com}. 
. mean trustpres if handled==1
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:263}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 3}trustpres {c |}{col 14}{res}{space 2}  2.60076{col 26}{space 2} .0598812{col 37}{space 5} 2.482851{col 51}{space 3}  2.71867
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store correct
{txt}
{com}. mean trustpres if handled==0
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:259}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 3}trustpres {c |}{col 14}{res}{space 2} 2.447876{col 26}{space 2} .0594345{col 37}{space 5} 2.330838{col 51}{space 3} 2.564915
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store incorrect
{txt}
{com}. 
. coefplot correct incorrect, /// 
>         vertical ciopts(recast(rcap)) xlabel(none) /// 
>         ytitle("Mean Trust") title("President") /// 
>         scheme(s1mono) name(presidency4)
{res}{txt}
{com}. 
. mean trustcongress if handled==1
{res}
{txt}{col 1}Mean estimation{col 45}{lalign 13:Number of obs}{col 58} = {res}{ralign 3:263}

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 15}{c |}       Mean{col 27}   Std. err.{col 39}     [95% con{col 52}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
trustcongress {c |}{col 15}{res}{space 2} 2.501901{col 27}{space 2}   .05411{col 38}{space 5} 2.395355{col 52}{space 3} 2.608447
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store correct
{txt}
{com}. mean trustcongress if handled==0
{res}
{txt}{col 1}Mean estimation{col 45}{lalign 13:Number of obs}{col 58} = {res}{ralign 3:259}

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 15}{c |}       Mean{col 27}   Std. err.{col 39}     [95% con{col 52}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
trustcongress {c |}{col 15}{res}{space 2} 2.382239{col 27}{space 2} .0567439{col 38}{space 5} 2.270499{col 52}{space 3}  2.49398
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.         est store incorrect
{txt}
{com}. 
. coefplot correct incorrect, /// 
>         vertical ciopts(recast(rcap)) xlabel(none) /// 
>         ytitle("Mean Trust") title("Congress") /// 
>         scheme(s1mono) name(congressional4)
{res}{txt}
{com}. 
. graph combine democracy4 presidency4 congressional4, /// 
>         altshrink ycommon rows(1) iscale(1.5) scheme(s1mono) /// 
>         note("The figure compares the means of post-treatment confidence in democratic institutions, trust in the president," /// 
>         "and trust in Congress, respectively, by treatment condition with 95% confidence intervals. The figure uses the" /// 
>         "4-point scale measure of each variable, replicating Figure 3 from the main text.")
{res}{txt}
{com}. 
. *Figure A5.3 Influence of Military Affiliation with 4-point measure
. ttest pretrust_1==pretrust_7, unpaired

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
pretru~1 {c |}{res}{col 12}    522{col 22} 3.768199{col 34} .0451724{col 46} 1.032069{col 58} 3.679457{col 70} 3.856942
{txt}pretru~7 {c |}{res}{col 12}    522{col 22} 2.720307{col 34} .0424971{col 46} .9709452{col 58}  2.63682{col 70} 2.803793
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}  1,044{col 22} 3.244253{col 34} .0349846{col 46} 1.130385{col 58} 3.175605{col 70} 3.312901
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} 1.047893{col 34} .0620206{col 58} .9261932{col 70} 1.169592
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}pretrust_1{txt}) - mean({res}pretrust_7{txt})                    t = {res} 16.8959
{txt}H0: diff = 0                                     Degrees of freedom = {res}    1042

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000
{txt}
{com}. ttest trustofficial, by(military)

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    262{col 22} 2.419847{col 34} .0532384{col 46} .8617384{col 58} 2.315016{col 70} 2.524679
       {txt}1 {c |}{res}{col 12}    260{col 22} 2.919231{col 34} .0470868{col 46} .7592514{col 58} 2.826509{col 70} 3.011952
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    522{col 22} 2.668582{col 34}  .037166{col 46}  .849144{col 58} 2.595569{col 70} 2.741596
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.4993834{col 34} .0711082{col 58}-.6390781{col 70}-.3596888
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -7.0229
{txt}H0: diff = 0                                     Degrees of freedom = {res}     520

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000
{txt}
{com}. ttest fire, by(military)

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. err.{col 47}Std. dev.{col 59}[95% conf. interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    262{col 22} 2.961832{col 34} .0594421{col 46} .9621542{col 58} 2.844785{col 70} 3.078879
       {txt}1 {c |}{res}{col 12}    260{col 22} 2.896154{col 34}  .053977{col 46} .8703529{col 58} 2.789864{col 70} 3.002443
{txt}{hline 9}{c +}{hline 68}
Combined {c |}{res}{col 12}    522{col 22} 2.929119{col 34} .0401486{col 46} .9172869{col 58} 2.850246{col 70} 3.007992
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0656782{col 34} .0803233{col 58}-.0921198{col 70} .2234762
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  0.8177
{txt}H0: diff = 0                                     Degrees of freedom = {res}     520

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.7930         {txt}Pr(|T| > |t|) = {res}0.4139          {txt}Pr(T > t) = {res}0.2070
{txt}
{com}. 
.         *pre-treatment trust
.         mean pretrust_1
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:522}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 2}pretrust_1 {c |}{col 14}{res}{space 2} 3.768199{col 26}{space 2} .0451724{col 37}{space 5} 3.679457{col 51}{space 3} 3.856942
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store military
{txt}
{com}.         mean pretrust_7
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:522}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 2}pretrust_7 {c |}{col 14}{res}{space 2} 2.720307{col 26}{space 2} .0424971{col 37}{space 5}  2.63682{col 51}{space 3} 2.803793
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store diplomats
{txt}
{com}. 
.         coefplot military diplomats, vertical xlabel(none) /// 
>                 ytitle("Mean Confident") title("Pre-Treatment" "Confidence") /// 
>                 scheme(s1mono) name(pretreat4)
{res}{txt}
{com}. 
.         *post-treatment trust
.         mean trustofficial if military==1
{res}
{txt}{col 1}Mean estimation{col 45}{lalign 13:Number of obs}{col 58} = {res}{ralign 3:260}

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 15}{c |}       Mean{col 27}   Std. err.{col 39}     [95% con{col 52}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
trustofficial {c |}{col 15}{res}{space 2} 2.919231{col 27}{space 2} .0470868{col 38}{space 5} 2.826509{col 52}{space 3} 3.011952
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store military
{txt}
{com}.         mean trustofficial if diplomat==1
{res}
{txt}{col 1}Mean estimation{col 45}{lalign 13:Number of obs}{col 58} = {res}{ralign 3:262}

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 15}{c |}       Mean{col 27}   Std. err.{col 39}     [95% con{col 52}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
trustofficial {c |}{col 15}{res}{space 2} 2.419847{col 27}{space 2} .0532384{col 38}{space 5} 2.315016{col 52}{space 3} 2.524679
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store diplomats
{txt}
{com}. 
.         coefplot military diplomats, vertical xlabel(none) /// 
>                 ytitle("Mean Trust") title("Trust in""Officials Who Mishandled") /// 
>                 scheme(s1mono) name(post4)
{res}{txt}
{com}. 
.         *Support for Firing
.         mean fire if military==1
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:260}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}fire {c |}{col 14}{res}{space 2} 2.896154{col 26}{space 2}  .053977{col 37}{space 5} 2.789864{col 51}{space 3} 3.002443
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store military
{txt}
{com}.         mean fire if diplomat==1
{res}
{txt}{col 1}Mean estimation{col 44}{lalign 13:Number of obs}{col 57} = {res}{ralign 3:262}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}fire {c |}{col 14}{res}{space 2} 2.961832{col 26}{space 2} .0594421{col 37}{space 5} 2.844785{col 51}{space 3} 3.078879
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}.                 est store diplomats
{txt}
{com}. 
.         coefplot military diplomats, vertical xlabel(none) /// 
>                 ytitle("Mean Support") title("Support for Firing""Officials Who Mishandled") /// 
>                 scheme(s1mono) name(fire4)
{res}{txt}
{com}.         
.         graph combine pretreat4 post4 fire4, altshrink ycommon rows(1) /// 
>                 iscale(1.4) scheme(s1mono) /// 
>                 note("Figure reports comparisons of means for three measures with 95% confidence intervals." /// 
>                 "The first panel reports the means of pre-treatment confidence in the military and in U.S. diplomats." /// 
>                 "The second panel reports the mean levels of post-treatment trust in the officials who mishandled documents," /// 
>                 "comparing the military and diplomat treatment conditions. The third panel reports the mean levels of" /// 
>                 "post-treatment support for firing the officials who mishandled documents, comparing the military and" /// 
>                 "diplomat treatment conditions. All panels use 4-point measures of the relevant variable, replicating" /// 
>                 "Figure 5 from the main text.", span)
{res}{txt}
{com}. 
. *A5.3 Are the stage two results condition on stage one treatment assignment?
. prtest firebi, by(mishandled)

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     263
                                                   1{txt}: Number of obs = {res}     259
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .7262357{col 28} .0274947{col 58} .6723471{col 70} .7801244
           {txt}1 {c |}{res}{col 17} .7413127{col 28} .0272106{col 58} .6879809{col 70} .7946446
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17} -.015077{col 28}  .038683{col 58}-.0908944{col 70} .0607404
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28}  .038694{col 38}   -0.39{col 49}0.697
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -0.3896
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.3484         {txt}Pr(|Z| > |z|) = {res}0.6968          {txt}Pr(Z > z) = {res}0.6516
{txt}
{com}. prtest trustofficialbi, by(mishandled) 

{txt}Two-sample test of proportions                     {res}0{txt}: Number of obs = {res}     263
                                                   1{txt}: Number of obs = {res}     259
{txt}{hline 13}{c TT}{hline 64}
       Group{col 14}{c |}{col 22}Mean{col 29}Std. err.{col 44}z{col 49}P>|z|{col 59}[95% conf. interval]
{hline 13}{c +}{hline 64}
           0 {c |}{res}{col 17} .6159696{col 28} .0299906{col 58} .5571892{col 70}   .67475
           {txt}1 {c |}{res}{col 17} .6525097{col 28}  .029588{col 58} .5945183{col 70}  .710501
{txt}{hline 13}{c +}{hline 64}
        diff {c |}{res}{col 17}-.0365401{col 28} .0421293{col 58} -.119112{col 70} .0460319
{txt}{col 14}{c |}{col 17}under H0:{res}{col 28} .0421665{col 38}   -0.87{col 49}0.386
{txt}{hline 13}{c BT}{hline 64}
        diff = prop({res}0{txt}) - prop({res}1{txt})                                  z = {res} -0.8666
{txt}    H0: diff = 0

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(Z < z) = {res}0.1931         {txt}Pr(|Z| > |z|) = {res}0.3862          {txt}Pr(Z > z) = {res}0.8069
{txt}
{com}. 
.         *Figure A5.4 Marginal Effects of Stage One Treatment Assignment on Stage Two Outcomes
.         logit firebi i.military i.highconfidence military##highconfidence

{res}{txt}Iteration 0:{space 2}Log likelihood = {res: -302.5132}  
Iteration 1:{space 2}Log likelihood = {res:-301.91108}  
Iteration 2:{space 2}Log likelihood = {res:-301.91062}  
Iteration 3:{space 2}Log likelihood = {res:-301.91062}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:522}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:1.21}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.7518}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-301.91062}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0020}

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 firebi{col 25}{c |} Coefficient{col 37}  Std. err.{col 49}      z{col 57}   P>|z|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}1.military {c |}{col 25}{res}{space 2} -.219459{col 37}{space 2} .2204442{col 48}{space 1}   -1.00{col 57}{space 3}0.319{col 65}{space 4}-.6515217{col 78}{space 3} .2126037
{txt}{space 7}1.highconfidence {c |}{col 25}{res}{space 2}-.0931652{col 37}{space 2} .3718734{col 48}{space 1}   -0.25{col 57}{space 3}0.802{col 65}{space 4}-.8220238{col 78}{space 3} .6356933
{txt}{space 23} {c |}
military#highconfidence {c |}
{space 19}1 1  {c |}{col 25}{res}{space 2} .3529904{col 37}{space 2} .5063476{col 48}{space 1}    0.70{col 57}{space 3}0.486{col 65}{space 4}-.6394326{col 78}{space 3} 1.345413
{txt}{space 23} {c |}
{space 18}_cons {c |}{col 25}{res}{space 2} 1.104766{col 37}{space 2} .1570143{col 48}{space 1}    7.04{col 57}{space 3}0.000{col 65}{space 4} .7970238{col 78}{space 3} 1.412509
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 margins military, at(highconfidence=(0 1))
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:522}
{txt}{col 1}Model VCE: {res:OIM}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(firebi), predict()}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 14:highconfidence} = {res:{ralign 1:0}}
{lalign 7:2._at: }{space 0}{lalign 14:highconfidence} = {res:{ralign 1:1}}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#military {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} .7511521{col 26}{space 2} .0293495{col 37}{space 1}   25.59{col 46}{space 3}0.000{col 54}{space 4} .6936281{col 67}{space 3} .8086761
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2} .7079208{col 26}{space 2} .0319939{col 37}{space 1}   22.13{col 46}{space 3}0.000{col 54}{space 4} .6452139{col 67}{space 3} .7706277
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} .7333333{col 26}{space 2} .0659218{col 37}{space 1}   11.12{col 46}{space 3}0.000{col 54}{space 4}  .604129{col 67}{space 3} .8625376
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .7586207{col 26}{space 2} .0561886{col 37}{space 1}   13.50{col 46}{space 3}0.000{col 54}{space 4}  .648493{col 67}{space 3} .8687484
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 marginsplot, scheme(s1mono) xtitle("High Pre-Treatment Confidence") /// 
>                 title("Predicted Probability of Support for Firing""by High Pre-Treatment Confidence") /// 
>                 name(predicthigh)
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:highconfidence military}{p_end}
{res}{txt}
{com}.         logit firebi i.military i.lowconfidence military##lowconfidence

{res}{txt}Iteration 0:{space 2}Log likelihood = {res: -302.5132}  
Iteration 1:{space 2}Log likelihood = {res:-301.99331}  
Iteration 2:{space 2}Log likelihood = {res:-301.99223}  
Iteration 3:{space 2}Log likelihood = {res:-301.99223}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:522}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:1.04}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.7911}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-301.99223}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0017}

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                firebi{col 24}{c |} Coefficient{col 36}  Std. err.{col 48}      z{col 56}   P>|z|{col 64}     [95% con{col 77}f. interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.military {c |}{col 24}{res}{space 2}-.0800427{col 36}{space 2} .2329131{col 47}{space 1}   -0.34{col 56}{space 3}0.731{col 64}{space 4}-.5365439{col 77}{space 3} .3764585
{txt}{space 7}1.lowconfidence {c |}{col 24}{res}{space 2} .0394025{col 36}{space 2} .3188462{col 47}{space 1}    0.12{col 56}{space 3}0.902{col 64}{space 4}-.5855245{col 77}{space 3} .6643296
{txt}{space 22} {c |}
military#lowconfidence {c |}
{space 18}1 1  {c |}{col 24}{res}{space 2}-.2527998{col 36}{space 2} .4442342{col 47}{space 1}   -0.57{col 56}{space 3}0.569{col 64}{space 4}-1.123483{col 77}{space 3} .6178833
{txt}{space 22} {c |}
{space 17}_cons {c |}{col 24}{res}{space 2} 1.077559{col 36}{space 2} .1671093{col 47}{space 1}    6.45{col 56}{space 3}0.000{col 64}{space 4} .7500306{col 77}{space 3} 1.405087
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 margins military, at(lowconfidence=(0 1))
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:522}
{txt}{col 1}Model VCE: {res:OIM}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(firebi), predict()}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 13:lowconfidence} = {res:{ralign 1:0}}
{lalign 7:2._at: }{space 0}{lalign 13:lowconfidence} = {res:{ralign 1:1}}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#military {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} .7460317{col 26}{space 2} .0316619{col 37}{space 1}   23.56{col 46}{space 3}0.000{col 54}{space 4} .6839755{col 67}{space 3}  .808088
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2} .7305699{col 26}{space 2} .0319356{col 37}{space 1}   22.88{col 46}{space 3}0.000{col 54}{space 4} .6679773{col 67}{space 3} .7931626
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} .7534247{col 26}{space 2} .0504468{col 37}{space 1}   14.94{col 46}{space 3}0.000{col 54}{space 4} .6545508{col 67}{space 3} .8522985
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .6865672{col 26}{space 2}  .056673{col 37}{space 1}   12.11{col 46}{space 3}0.000{col 54}{space 4} .5754901{col 67}{space 3} .7976442
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 marginsplot, scheme(s1mono) xtitle("Low Pre-Treatment Confidence") /// 
>                 title("Predicted Probability of Support for Firing""by Low Pre-Treatment Confidence") /// 
>                 name(predictlow)
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:lowconfidence military}{p_end}
{res}{txt}
{com}.         graph combine predicthigh predictlow, altshrink ycommon scheme(s1mono)
{res}{txt}
{com}. 
. *A5.4 Tests for Additional Moderators
.         *Figure A5.5 Marginal Effects of Republican Identification on Treatment
.         logit institutionsbi i.mishandled i.republican mishandled##republican

{res}{txt}Iteration 0:{space 2}Log likelihood = {res:-347.43341}  
Iteration 1:{space 2}Log likelihood = {res:-333.65856}  
Iteration 2:{space 2}Log likelihood = {res:-333.58114}  
Iteration 3:{space 2}Log likelihood = {res:-333.58112}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:522}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:27.70}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-333.58112}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0399}

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       institutionsbi{col 23}{c |} Coefficient{col 35}  Std. err.{col 47}      z{col 55}   P>|z|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.mishandled {c |}{col 23}{res}{space 2}-.6343063{col 35}{space 2} .2627449{col 46}{space 1}   -2.41{col 55}{space 3}0.016{col 63}{space 4}-1.149277{col 76}{space 3}-.1193358
{txt}{space 9}1.republican {c |}{col 23}{res}{space 2}-.6971072{col 35}{space 2} .2707219{col 46}{space 1}   -2.57{col 55}{space 3}0.010{col 63}{space 4}-1.227712{col 76}{space 3} -.166502
{txt}{space 21} {c |}
mishandled#republican {c |}
{space 17}1 1  {c |}{col 23}{res}{space 2}-.0258929{col 35}{space 2} .3708781{col 46}{space 1}   -0.07{col 55}{space 3}0.944{col 63}{space 4}-.7528007{col 76}{space 3} .7010149
{txt}{space 21} {c |}
{space 16}_cons {c |}{col 23}{res}{space 2} 1.145132{col 35}{space 2} .1940679{col 46}{space 1}    5.90{col 55}{space 3}0.000{col 63}{space 4} .7647659{col 76}{space 3} 1.525498
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 margins republican, at(mishandled=(0 1))
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:522}
{txt}{col 1}Model VCE: {res:OIM}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(institutionsbi), predict()}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 10:mishandled} = {res:{ralign 1:0}}
{lalign 7:2._at: }{space 0}{lalign 10:mishandled} = {res:{ralign 1:1}}

{res}{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28} Delta-method
{col 16}{c |}     Margin{col 28}   std. err.{col 40}      z{col 48}   P>|z|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#republican {c |}
{space 10}1 0  {c |}{col 16}{res}{space 2} .7586206{col 28}{space 2} .0355368{col 39}{space 1}   21.35{col 48}{space 3}0.000{col 56}{space 4} .6889698{col 69}{space 3} .8282715
{txt}{space 10}1 1  {c |}{col 16}{res}{space 2} .6101695{col 28}{space 2} .0448975{col 39}{space 1}   13.59{col 48}{space 3}0.000{col 56}{space 4}  .522172{col 69}{space 3}  .698167
{txt}{space 10}2 0  {c |}{col 16}{res}{space 2}     .625{col 28}{space 2} .0415132{col 39}{space 1}   15.06{col 48}{space 3}0.000{col 56}{space 4} .5436356{col 69}{space 3} .7063644
{txt}{space 10}2 1  {c |}{col 16}{res}{space 2} .4471545{col 28}{space 2}  .044831{col 39}{space 1}    9.97{col 48}{space 3}0.000{col 56}{space 4} .3592874{col 69}{space 3} .5350216
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 marginsplot, xtitle("Incorrectly Handled Treatment") /// 
>                 title("Predicted Probabilities of""Confidence in Institutions by Party ID") /// 
>                 scheme(s1mono) name(predictparti)
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:mishandled republican}{p_end}
{res}{txt}
{com}.         logit firebi i.military i.republican military##republican

{res}{txt}Iteration 0:{space 2}Log likelihood = {res: -302.5132}  
Iteration 1:{space 2}Log likelihood = {res:-302.13804}  
Iteration 2:{space 2}Log likelihood = {res:-302.13775}  
Iteration 3:{space 2}Log likelihood = {res:-302.13775}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:522}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:0.75}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.8612}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-302.13775}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0012}

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             firebi{col 21}{c |} Coefficient{col 33}  Std. err.{col 45}      z{col 53}   P>|z|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.military {c |}{col 21}{res}{space 2}-.0760901{col 33}{space 2} .2688757{col 44}{space 1}   -0.28{col 53}{space 3}0.777{col 61}{space 4}-.6030769{col 74}{space 3} .4508966
{txt}{space 7}1.republican {c |}{col 21}{res}{space 2} .1210779{col 33}{space 2} .2855493{col 44}{space 1}    0.42{col 53}{space 3}0.672{col 61}{space 4}-.4385885{col 74}{space 3} .6807443
{txt}{space 19} {c |}
military#republican {c |}
{space 15}1 1  {c |}{col 21}{res}{space 2}-.1542563{col 33}{space 2} .3981269{col 44}{space 1}   -0.39{col 53}{space 3}0.698{col 61}{space 4}-.9345707{col 74}{space 3}  .626058
{txt}{space 19} {c |}
{space 14}_cons {c |}{col 21}{res}{space 2} 1.031602{col 33}{space 2} .1941102{col 44}{space 1}    5.31{col 53}{space 3}0.000{col 61}{space 4} .6511526{col 74}{space 3} 1.412051
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 margins republican, at(military=(0 1))
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:522}
{txt}{col 1}Model VCE: {res:OIM}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(firebi), predict()}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 8:military} = {res:{ralign 1:0}}
{lalign 7:2._at: }{space 0}{lalign 8:military} = {res:{ralign 1:1}}

{res}{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28} Delta-method
{col 16}{c |}     Margin{col 28}   std. err.{col 40}      z{col 48}   P>|z|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#republican {c |}
{space 10}1 0  {c |}{col 16}{res}{space 2} .7372263{col 28}{space 2} .0376037{col 39}{space 1}   19.61{col 48}{space 3}0.000{col 56}{space 4} .6635243{col 69}{space 3} .8109283
{txt}{space 10}1 1  {c |}{col 16}{res}{space 2}      .76{col 28}{space 2} .0381995{col 39}{space 1}   19.90{col 48}{space 3}0.000{col 56}{space 4} .6851304{col 69}{space 3} .8348696
{txt}{space 10}2 0  {c |}{col 16}{res}{space 2} .7222222{col 28}{space 2} .0373253{col 39}{space 1}   19.35{col 48}{space 3}0.000{col 56}{space 4}  .649066{col 69}{space 3} .7953784
{txt}{space 10}2 1  {c |}{col 16}{res}{space 2} .7155172{col 28}{space 2} .0418899{col 39}{space 1}   17.08{col 48}{space 3}0.000{col 56}{space 4} .6334146{col 69}{space 3} .7976199
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 marginsplot, xtitle("Military Official Treatment") /// 
>                 title("Predicted Probabilities of""Support for Firing by Party ID") /// 
>                 scheme(s1mono) name(predictpartf)
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:military republican}{p_end}
{res}{txt}
{com}.         graph combine predictparti predictpartf, /// 
>                 altshrink ycommon rows(1) iscale(1.1) scheme(s1mono)
{res}{txt}
{com}.                 
.         *Figure A5.6 Marginal Effects of Copartisanship on Treatment
.         logit institutionsbi i.mishandled i.copartisan mishandled##copartisan

{res}{txt}Iteration 0:{space 2}Log likelihood = {res:-347.43341}  
Iteration 1:{space 2}Log likelihood = {res:-338.93442}  
Iteration 2:{space 2}Log likelihood = {res:-338.89949}  
Iteration 3:{space 2}Log likelihood = {res:-338.89949}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:522}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:17.07}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0007}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-338.89949}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0246}

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       institutionsbi{col 23}{c |} Coefficient{col 35}  Std. err.{col 47}      z{col 55}   P>|z|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.mishandled {c |}{col 23}{res}{space 2}-.6065902{col 35}{space 2} .2423347{col 46}{space 1}   -2.50{col 55}{space 3}0.012{col 63}{space 4}-1.081557{col 76}{space 3}-.1316231
{txt}{space 9}1.copartisan {c |}{col 23}{res}{space 2} .4340726{col 35}{space 2} .2724825{col 46}{space 1}    1.59{col 55}{space 3}0.111{col 63}{space 4}-.0999833{col 76}{space 3} .9681285
{txt}{space 21} {c |}
mishandled#copartisan {c |}
{space 17}1 1  {c |}{col 23}{res}{space 2}-.0997521{col 35}{space 2} .3711594{col 46}{space 1}   -0.27{col 55}{space 3}0.788{col 63}{space 4}-.8272112{col 76}{space 3}  .627707
{txt}{space 21} {c |}
{space 16}_cons {c |}{col 23}{res}{space 2} .6205765{col 35}{space 2} .1753644{col 46}{space 1}    3.54{col 55}{space 3}0.000{col 63}{space 4} .2768685{col 76}{space 3} .9642845
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 margins copartisan, at(mishandled=(0 1))
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:522}
{txt}{col 1}Model VCE: {res:OIM}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(institutionsbi), predict()}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 10:mishandled} = {res:{ralign 1:0}}
{lalign 7:2._at: }{space 0}{lalign 10:mishandled} = {res:{ralign 1:1}}

{res}{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28} Delta-method
{col 16}{c |}     Margin{col 28}   std. err.{col 40}      z{col 48}   P>|z|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#copartisan {c |}
{space 10}1 0  {c |}{col 16}{res}{space 2} .6503497{col 28}{space 2}  .039877{col 39}{space 1}   16.31{col 48}{space 3}0.000{col 56}{space 4} .5721922{col 69}{space 3} .7285071
{txt}{space 10}1 1  {c |}{col 16}{res}{space 2} .7416667{col 28}{space 2}  .039958{col 39}{space 1}   18.56{col 48}{space 3}0.000{col 56}{space 4} .6633504{col 69}{space 3} .8199829
{txt}{space 10}2 0  {c |}{col 16}{res}{space 2} .5034965{col 28}{space 2} .0418111{col 39}{space 1}   12.04{col 48}{space 3}0.000{col 56}{space 4} .4215483{col 69}{space 3} .5854447
{txt}{space 10}2 1  {c |}{col 16}{res}{space 2} .5862069{col 28}{space 2} .0457286{col 39}{space 1}   12.82{col 48}{space 3}0.000{col 56}{space 4} .4965804{col 69}{space 3} .6758333
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 marginsplot, xtitle("Incorrectly Handled Treatment") /// 
>                 title("Predicted Probabilities of""Confidence in Institutions by Copartisanship") /// 
>                 scheme(s1mono) name(predictcoi)
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:mishandled copartisan}{p_end}
{res}{txt}
{com}.         logit firebi i.military i.copartisan military##copartisan

{res}{txt}Iteration 0:{space 2}Log likelihood = {res: -302.5132}  
Iteration 1:{space 2}Log likelihood = {res:-302.21288}  
Iteration 2:{space 2}Log likelihood = {res:-302.21275}  
Iteration 3:{space 2}Log likelihood = {res:-302.21275}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:522}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:0.60}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.8962}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-302.21275}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0010}

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             firebi{col 21}{c |} Coefficient{col 33}  Std. err.{col 45}      z{col 53}   P>|z|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.military {c |}{col 21}{res}{space 2}-.1258176{col 33}{space 2} .2667897{col 44}{space 1}   -0.47{col 53}{space 3}0.637{col 61}{space 4}-.6487158{col 74}{space 3} .3970806
{txt}{space 7}1.copartisan {c |}{col 21}{res}{space 2} .0594296{col 33}{space 2} .2865162{col 44}{space 1}    0.21{col 53}{space 3}0.836{col 61}{space 4}-.5021318{col 74}{space 3} .6209911
{txt}{space 19} {c |}
military#copartisan {c |}
{space 15}1 1  {c |}{col 21}{res}{space 2}-.0493793{col 33}{space 2} .3987019{col 44}{space 1}   -0.12{col 53}{space 3}0.901{col 61}{space 4}-.8308206{col 74}{space 3} .7320621
{txt}{space 19} {c |}
{space 14}_cons {c |}{col 21}{res}{space 2} 1.061911{col 33}{space 2} .1907166{col 44}{space 1}    5.57{col 53}{space 3}0.000{col 61}{space 4} .6881133{col 74}{space 3} 1.435709
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 margins copartisan, at(military=(0 1))
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:522}
{txt}{col 1}Model VCE: {res:OIM}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(firebi), predict()}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 8:military} = {res:{ralign 1:0}}
{lalign 7:2._at: }{space 0}{lalign 8:military} = {res:{ralign 1:1}}

{res}{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28} Delta-method
{col 16}{c |}     Margin{col 28}   std. err.{col 40}      z{col 48}   P>|z|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#copartisan {c |}
{space 10}1 0  {c |}{col 16}{res}{space 2} .7430556{col 28}{space 2} .0364124{col 39}{space 1}   20.41{col 48}{space 3}0.000{col 56}{space 4} .6716886{col 69}{space 3} .8144225
{txt}{space 10}1 1  {c |}{col 16}{res}{space 2} .7542373{col 28}{space 2} .0396343{col 39}{space 1}   19.03{col 48}{space 3}0.000{col 56}{space 4} .6765555{col 69}{space 3} .8319191
{txt}{space 10}2 0  {c |}{col 16}{res}{space 2} .7183099{col 28}{space 2} .0377483{col 39}{space 1}   19.03{col 48}{space 3}0.000{col 56}{space 4} .6443245{col 69}{space 3} .7922952
{txt}{space 10}2 1  {c |}{col 16}{res}{space 2}  .720339{col 28}{space 2} .0413184{col 39}{space 1}   17.43{col 48}{space 3}0.000{col 56}{space 4} .6393564{col 69}{space 3} .8013215
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 marginsplot, xtitle("Military Official Treatment") /// 
>                 title("Predicted Probabilities of""Support for Firing by Copartisanship") /// 
>                 scheme(s1mono) name(predictcof)
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:military copartisan}{p_end}
{res}{txt}
{com}.         graph combine predictcoi predictcof, altshrink ycommon rows(1) iscale(1.1) scheme(s1mono)
{res}{txt}
{com}.         
.         *Figure A5.7 Marginal Effects of Pre-Treatment Confidence on Treatment
.         logit firebi i.military i.highconfidence military##highconfidence

{res}{txt}Iteration 0:{space 2}Log likelihood = {res: -302.5132}  
Iteration 1:{space 2}Log likelihood = {res:-301.91108}  
Iteration 2:{space 2}Log likelihood = {res:-301.91062}  
Iteration 3:{space 2}Log likelihood = {res:-301.91062}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:522}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:1.21}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.7518}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-301.91062}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0020}

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 firebi{col 25}{c |} Coefficient{col 37}  Std. err.{col 49}      z{col 57}   P>|z|{col 65}     [95% con{col 78}f. interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}1.military {c |}{col 25}{res}{space 2} -.219459{col 37}{space 2} .2204442{col 48}{space 1}   -1.00{col 57}{space 3}0.319{col 65}{space 4}-.6515217{col 78}{space 3} .2126037
{txt}{space 7}1.highconfidence {c |}{col 25}{res}{space 2}-.0931652{col 37}{space 2} .3718734{col 48}{space 1}   -0.25{col 57}{space 3}0.802{col 65}{space 4}-.8220238{col 78}{space 3} .6356933
{txt}{space 23} {c |}
military#highconfidence {c |}
{space 19}1 1  {c |}{col 25}{res}{space 2} .3529904{col 37}{space 2} .5063476{col 48}{space 1}    0.70{col 57}{space 3}0.486{col 65}{space 4}-.6394326{col 78}{space 3} 1.345413
{txt}{space 23} {c |}
{space 18}_cons {c |}{col 25}{res}{space 2} 1.104766{col 37}{space 2} .1570143{col 48}{space 1}    7.04{col 57}{space 3}0.000{col 65}{space 4} .7970238{col 78}{space 3} 1.412509
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 margins military, at(highconfidence=(0 1))
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:522}
{txt}{col 1}Model VCE: {res:OIM}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(firebi), predict()}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 14:highconfidence} = {res:{ralign 1:0}}
{lalign 7:2._at: }{space 0}{lalign 14:highconfidence} = {res:{ralign 1:1}}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#military {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} .7511521{col 26}{space 2} .0293495{col 37}{space 1}   25.59{col 46}{space 3}0.000{col 54}{space 4} .6936281{col 67}{space 3} .8086761
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2} .7079208{col 26}{space 2} .0319939{col 37}{space 1}   22.13{col 46}{space 3}0.000{col 54}{space 4} .6452139{col 67}{space 3} .7706277
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} .7333333{col 26}{space 2} .0659218{col 37}{space 1}   11.12{col 46}{space 3}0.000{col 54}{space 4}  .604129{col 67}{space 3} .8625376
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .7586207{col 26}{space 2} .0561886{col 37}{space 1}   13.50{col 46}{space 3}0.000{col 54}{space 4}  .648493{col 67}{space 3} .8687484
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 marginsplot, scheme(s1mono) xtitle("High Pre-Treatment Confidence") /// 
>                 title("Predicted Probability of Support for Firing""by High Pre-Treatment Confidence") /// 
>                 name(predicthighpre)
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:highconfidence military}{p_end}
{res}{txt}
{com}.         logit firebi i.military i.lowconfidence military##lowconfidence

{res}{txt}Iteration 0:{space 2}Log likelihood = {res: -302.5132}  
Iteration 1:{space 2}Log likelihood = {res:-301.99331}  
Iteration 2:{space 2}Log likelihood = {res:-301.99223}  
Iteration 3:{space 2}Log likelihood = {res:-301.99223}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:522}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:1.04}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.7911}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-301.99223}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0017}

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                firebi{col 24}{c |} Coefficient{col 36}  Std. err.{col 48}      z{col 56}   P>|z|{col 64}     [95% con{col 77}f. interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.military {c |}{col 24}{res}{space 2}-.0800427{col 36}{space 2} .2329131{col 47}{space 1}   -0.34{col 56}{space 3}0.731{col 64}{space 4}-.5365439{col 77}{space 3} .3764585
{txt}{space 7}1.lowconfidence {c |}{col 24}{res}{space 2} .0394025{col 36}{space 2} .3188462{col 47}{space 1}    0.12{col 56}{space 3}0.902{col 64}{space 4}-.5855245{col 77}{space 3} .6643296
{txt}{space 22} {c |}
military#lowconfidence {c |}
{space 18}1 1  {c |}{col 24}{res}{space 2}-.2527998{col 36}{space 2} .4442342{col 47}{space 1}   -0.57{col 56}{space 3}0.569{col 64}{space 4}-1.123483{col 77}{space 3} .6178833
{txt}{space 22} {c |}
{space 17}_cons {c |}{col 24}{res}{space 2} 1.077559{col 36}{space 2} .1671093{col 47}{space 1}    6.45{col 56}{space 3}0.000{col 64}{space 4} .7500306{col 77}{space 3} 1.405087
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 margins military, at(lowconfidence=(0 1))
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:522}
{txt}{col 1}Model VCE: {res:OIM}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(firebi), predict()}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 13:lowconfidence} = {res:{ralign 1:0}}
{lalign 7:2._at: }{space 0}{lalign 13:lowconfidence} = {res:{ralign 1:1}}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#military {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} .7460317{col 26}{space 2} .0316619{col 37}{space 1}   23.56{col 46}{space 3}0.000{col 54}{space 4} .6839755{col 67}{space 3}  .808088
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2} .7305699{col 26}{space 2} .0319356{col 37}{space 1}   22.88{col 46}{space 3}0.000{col 54}{space 4} .6679773{col 67}{space 3} .7931626
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} .7534247{col 26}{space 2} .0504468{col 37}{space 1}   14.94{col 46}{space 3}0.000{col 54}{space 4} .6545508{col 67}{space 3} .8522985
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .6865672{col 26}{space 2}  .056673{col 37}{space 1}   12.11{col 46}{space 3}0.000{col 54}{space 4} .5754901{col 67}{space 3} .7976442
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 marginsplot, scheme(s1mono) xtitle("Low Pre-Treatment Confidence") /// 
>                 title("Predicted Probability of Support for Firing""by Low Pre-Treatment Confidence") /// 
>                 name(predictlowpre)
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:lowconfidence military}{p_end}
{res}{txt}
{com}.         graph combine predicthighpre predictlowpre, altshrink ycommon scheme(s1mono)
{res}{txt}
{com}.         
.         *Figure A5.8 Marginal Effects of Attention to News on Treatment
.         logit institutionsbi i.mishandled i.highnews mishandled##highnews

{res}{txt}Iteration 0:{space 2}Log likelihood = {res:-347.43341}  
Iteration 1:{space 2}Log likelihood = {res:-340.05518}  
Iteration 2:{space 2}Log likelihood = {res:-340.01768}  
Iteration 3:{space 2}Log likelihood = {res:-340.01767}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:522}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:14.83}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0020}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-340.01767}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0213}

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     institutionsbi{col 21}{c |} Coefficient{col 33}  Std. err.{col 45}      z{col 53}   P>|z|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}1.mishandled {c |}{col 21}{res}{space 2}-.5771825{col 33}{space 2} .2077613{col 44}{space 1}   -2.78{col 53}{space 3}0.005{col 61}{space 4}-.9843872{col 74}{space 3}-.1699779
{txt}{space 9}1.highnews {c |}{col 21}{res}{space 2} .4812838{col 33}{space 2}  .349398{col 44}{space 1}    1.38{col 53}{space 3}0.168{col 61}{space 4}-.2035238{col 74}{space 3} 1.166091
{txt}{space 19} {c |}
mishandled#highnews {c |}
{space 15}1 1  {c |}{col 21}{res}{space 2} -.389493{col 33}{space 2} .4486008{col 44}{space 1}   -0.87{col 53}{space 3}0.385{col 61}{space 4}-1.268734{col 74}{space 3} .4897484
{txt}{space 19} {c |}
{space 14}_cons {c |}{col 21}{res}{space 2} .7149662{col 33}{space 2} .1479869{col 44}{space 1}    4.83{col 53}{space 3}0.000{col 61}{space 4} .4249172{col 74}{space 3} 1.005015
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 margins highnews, at(mishandled=(0 1))
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:522}
{txt}{col 1}Model VCE: {res:OIM}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(institutionsbi), predict()}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 10:mishandled} = {res:{ralign 1:0}}
{lalign 7:2._at: }{space 0}{lalign 10:mishandled} = {res:{ralign 1:1}}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#highnews {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} .6714976{col 26}{space 2} .0326442{col 37}{space 1}   20.57{col 46}{space 3}0.000{col 54}{space 4} .6075161{col 67}{space 3} .7354791
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2}  .767857{col 26}{space 2} .0564188{col 37}{space 1}   13.61{col 46}{space 3}0.000{col 54}{space 4} .6572782{col 67}{space 3} .8784359
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} .5343915{col 26}{space 2} .0362835{col 37}{space 1}   14.73{col 46}{space 3}0.000{col 54}{space 4} .4632772{col 67}{space 3} .6055059
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .5571429{col 26}{space 2} .0593699{col 37}{space 1}    9.38{col 46}{space 3}0.000{col 54}{space 4} .4407801{col 67}{space 3} .6735057
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 marginsplot, xtitle("Incorrectly Handled Treatment") /// 
>                 title("Predicted Probabilities of""Confidence in Institutions by News Attention") /// 
>                 scheme(s1mono) name(newsconmargins)
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:mishandled highnews}{p_end}
{res}{txt}
{com}.         logit firebi i.military i.highnews military##highnews

{res}{txt}Iteration 0:{space 2}Log likelihood = {res: -302.5132}  
Iteration 1:{space 2}Log likelihood = {res:-301.95981}  
Iteration 2:{space 2}Log likelihood = {res:-301.95815}  
Iteration 3:{space 2}Log likelihood = {res:-301.95815}  
{res}
{txt}{col 1}Logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:522}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:1.11}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.7746}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-301.95815}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0018}

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           firebi{col 19}{c |} Coefficient{col 31}  Std. err.{col 43}      z{col 51}   P>|z|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}1.military {c |}{col 19}{res}{space 2}-.1065136{col 31}{space 2}  .225733{col 42}{space 1}   -0.47{col 51}{space 3}0.637{col 59}{space 4}-.5489422{col 72}{space 3} .3359149
{txt}{space 7}1.highnews {c |}{col 19}{res}{space 2} .2515438{col 31}{space 2} .3518224{col 42}{space 1}    0.71{col 51}{space 3}0.475{col 59}{space 4}-.4380154{col 72}{space 3} .9411031
{txt}{space 17} {c |}
military#highnews {c |}
{space 13}1 1  {c |}{col 19}{res}{space 2}-.1978553{col 31}{space 2} .4749147{col 42}{space 1}   -0.42{col 51}{space 3}0.677{col 59}{space 4}-1.128671{col 72}{space 3} .7329603
{txt}{space 17} {c |}
{space 12}_cons {c |}{col 19}{res}{space 2} 1.033654{col 31}{space 2} .1599354{col 42}{space 1}    6.46{col 51}{space 3}0.000{col 59}{space 4} .7201868{col 72}{space 3} 1.347122
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                 margins highnews, at(military=(0 1))
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:522}
{txt}{col 1}Model VCE: {res:OIM}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(firebi), predict()}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 8:military} = {res:{ralign 1:0}}
{lalign 7:2._at: }{space 0}{lalign 8:military} = {res:{ralign 1:1}}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#highnews {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} .7376238{col 26}{space 2} .0309531{col 37}{space 1}   23.83{col 46}{space 3}0.000{col 54}{space 4} .6769568{col 67}{space 3} .7982907
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2} .7833333{col 26}{space 2} .0531856{col 37}{space 1}   14.73{col 46}{space 3}0.000{col 54}{space 4} .6790916{col 67}{space 3} .8875751
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} .7164948{col 26}{space 2} .0323583{col 37}{space 1}   22.14{col 46}{space 3}0.000{col 54}{space 4} .6530737{col 67}{space 3}  .779916
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .7272727{col 26}{space 2} .0548202{col 37}{space 1}   13.27{col 46}{space 3}0.000{col 54}{space 4}  .619827{col 67}{space 3} .8347184
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.                 marginsplot, xtitle("Military Official Treatment") /// 
>                 title("Predicted Probabilities of""Support for Firing by News Attention") /// 
>                 scheme(s1mono) name(newsmilmargins)
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:military highnews}{p_end}
{res}{txt}
{com}. 
.         graph combine newsconmargins newsmilmargins, altshrink ycommon rows(1) scheme(s1mono)
{res}{txt}
{com}. 
. *A5.5 Estimating Treatment Effects with Demographic Controls
.         *Confidence in Institutions
.         reg institutionsbi mishandled male age democrat republican white college

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       522
{txt}{hline 13}{c +}{hline 34}   F(7, 514)       = {res}    10.60
{txt}       Model {c |} {res} 15.5656248         7  2.22366068   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 107.806023       514  .209739344   {txt}R-squared       ={res}    0.1262
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1143
{txt}       Total {c |} {res} 123.371648       521  .236797788   {txt}Root MSE        =   {res} .45797

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}institutio~i{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}mishandled {c |}{col 14}{res}{space 2}-.1565915{col 26}{space 2} .0402266{col 37}{space 1}   -3.89{col 46}{space 3}0.000{col 54}{space 4}-.2356203{col 67}{space 3}-.0775627
{txt}{space 8}male {c |}{col 14}{res}{space 2} .0479731{col 26}{space 2} .0419404{col 37}{space 1}    1.14{col 46}{space 3}0.253{col 54}{space 4}-.0344226{col 67}{space 3} .1303688
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0580619{col 26}{space 2} .0126895{col 37}{space 1}    4.58{col 46}{space 3}0.000{col 54}{space 4} .0331323{col 67}{space 3} .0829916
{txt}{space 4}democrat {c |}{col 14}{res}{space 2} .1878652{col 26}{space 2} .0649704{col 37}{space 1}    2.89{col 46}{space 3}0.004{col 54}{space 4}  .060225{col 67}{space 3} .3155053
{txt}{space 2}republican {c |}{col 14}{res}{space 2}-.0413873{col 26}{space 2} .0650915{col 37}{space 1}   -0.64{col 46}{space 3}0.525{col 54}{space 4}-.1692655{col 67}{space 3} .0864909
{txt}{space 7}white {c |}{col 14}{res}{space 2}-.0338216{col 26}{space 2} .0594391{col 37}{space 1}   -0.57{col 46}{space 3}0.570{col 54}{space 4}-.1505951{col 67}{space 3}  .082952
{txt}{space 5}college {c |}{col 14}{res}{space 2} .0986078{col 26}{space 2} .0420511{col 37}{space 1}    2.34{col 46}{space 3}0.019{col 54}{space 4} .0159946{col 67}{space 3}  .181221
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3173681{col 26}{space 2} .0876782{col 37}{space 1}    3.62{col 46}{space 3}0.000{col 54}{space 4} .1451164{col 67}{space 3} .4896197
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
.         *Trust President
.         reg trustpresbi mishandled male age democrat republican white college

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       522
{txt}{hline 13}{c +}{hline 34}   F(7, 514)       = {res}     9.90
{txt}       Model {c |} {res}  15.251536         7  2.17879086   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 113.162257       514  .220160033   {txt}R-squared       ={res}    0.1188
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1068
{txt}       Total {c |} {res} 128.413793       521  .246475611   {txt}Root MSE        =   {res} .46921

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} trustpresbi{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}mishandled {c |}{col 14}{res}{space 2}-.1234858{col 26}{space 2} .0412138{col 37}{space 1}   -3.00{col 46}{space 3}0.003{col 54}{space 4} -.204454{col 67}{space 3}-.0425176
{txt}{space 8}male {c |}{col 14}{res}{space 2}-.0041811{col 26}{space 2} .0429697{col 37}{space 1}   -0.10{col 46}{space 3}0.923{col 54}{space 4}-.0885988{col 67}{space 3} .0802367
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0487134{col 26}{space 2} .0130009{col 37}{space 1}    3.75{col 46}{space 3}0.000{col 54}{space 4} .0231719{col 67}{space 3} .0742548
{txt}{space 4}democrat {c |}{col 14}{res}{space 2} .2094841{col 26}{space 2} .0665648{col 37}{space 1}    3.15{col 46}{space 3}0.002{col 54}{space 4} .0787115{col 67}{space 3} .3402566
{txt}{space 2}republican {c |}{col 14}{res}{space 2}-.1032993{col 26}{space 2} .0666889{col 37}{space 1}   -1.55{col 46}{space 3}0.122{col 54}{space 4}-.2343158{col 67}{space 3} .0277171
{txt}{space 7}white {c |}{col 14}{res}{space 2}  .029762{col 26}{space 2} .0608978{col 37}{space 1}    0.49{col 46}{space 3}0.625{col 54}{space 4}-.0898773{col 67}{space 3} .1494013
{txt}{space 5}college {c |}{col 14}{res}{space 2} .0268416{col 26}{space 2} .0430831{col 37}{space 1}    0.62{col 46}{space 3}0.534{col 54}{space 4} -.057799{col 67}{space 3} .1114823
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3090932{col 26}{space 2} .0898299{col 37}{space 1}    3.44{col 46}{space 3}0.001{col 54}{space 4} .1326143{col 67}{space 3}  .485572
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         *Trust Congress
.         reg trustcongressbi mishandled male age democrat republican white college

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       522
{txt}{hline 13}{c +}{hline 34}   F(7, 514)       = {res}     3.98
{txt}       Model {c |} {res} 6.69611106         7  .956587294   {txt}Prob > F        ={res}    0.0003
{txt}    Residual {c |} {res} 123.480134       514  .240233724   {txt}R-squared       ={res}    0.0514
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0385
{txt}       Total {c |} {res} 130.176245       521  .249858436   {txt}Root MSE        =   {res} .49014

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}trustcongr~i{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}mishandled {c |}{col 14}{res}{space 2}-.0751948{col 26}{space 2} .0430517{col 37}{space 1}   -1.75{col 46}{space 3}0.081{col 54}{space 4}-.1597737{col 67}{space 3} .0093842
{txt}{space 8}male {c |}{col 14}{res}{space 2}-.0573321{col 26}{space 2} .0448859{col 37}{space 1}   -1.28{col 46}{space 3}0.202{col 54}{space 4}-.1455144{col 67}{space 3} .0308503
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0190556{col 26}{space 2} .0135807{col 37}{space 1}    1.40{col 46}{space 3}0.161{col 54}{space 4}-.0076248{col 67}{space 3} .0457361
{txt}{space 4}democrat {c |}{col 14}{res}{space 2} .1403901{col 26}{space 2} .0695332{col 37}{space 1}    2.02{col 46}{space 3}0.044{col 54}{space 4} .0037857{col 67}{space 3} .2769944
{txt}{space 2}republican {c |}{col 14}{res}{space 2} -.036563{col 26}{space 2} .0696629{col 37}{space 1}   -0.52{col 46}{space 3}0.600{col 54}{space 4} -.173422{col 67}{space 3}  .100296
{txt}{space 7}white {c |}{col 14}{res}{space 2}-.0405904{col 26}{space 2} .0636135{col 37}{space 1}   -0.64{col 46}{space 3}0.524{col 54}{space 4} -.165565{col 67}{space 3} .0843841
{txt}{space 5}college {c |}{col 14}{res}{space 2} .0984974{col 26}{space 2} .0450044{col 37}{space 1}    2.19{col 46}{space 3}0.029{col 54}{space 4} .0100822{col 67}{space 3} .1869125
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4464876{col 26}{space 2} .0938358{col 37}{space 1}    4.76{col 46}{space 3}0.000{col 54}{space 4} .2621387{col 67}{space 3} .6308365
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         *Support Firing
.         reg firebi military male age democrat republican white college

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       522
{txt}{hline 13}{c +}{hline 34}   F(7, 514)       = {res}     3.46
{txt}       Model {c |} {res} 4.59574298         7  .656534711   {txt}Prob > F        ={res}    0.0012
{txt}    Residual {c |} {res} 97.3908471       514  .189476356   {txt}R-squared       ={res}    0.0451
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0321
{txt}       Total {c |} {res}  101.98659       521  .195751612   {txt}Root MSE        =   {res} .43529

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      firebi{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}military {c |}{col 14}{res}{space 2}-.0260985{col 26}{space 2} .0383186{col 37}{space 1}   -0.68{col 46}{space 3}0.496{col 54}{space 4}-.1013789{col 67}{space 3} .0491818
{txt}{space 8}male {c |}{col 14}{res}{space 2}   .01043{col 26}{space 2} .0399004{col 37}{space 1}    0.26{col 46}{space 3}0.794{col 54}{space 4}-.0679579{col 67}{space 3}  .088818
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0219787{col 26}{space 2}  .012054{col 37}{space 1}    1.82{col 46}{space 3}0.069{col 54}{space 4}-.0017025{col 67}{space 3} .0456598
{txt}{space 4}democrat {c |}{col 14}{res}{space 2} .0313738{col 26}{space 2} .0617287{col 37}{space 1}    0.51{col 46}{space 3}0.611{col 54}{space 4}-.0898978{col 67}{space 3} .1526453
{txt}{space 2}republican {c |}{col 14}{res}{space 2}-.0202675{col 26}{space 2}  .061872{col 37}{space 1}   -0.33{col 46}{space 3}0.743{col 54}{space 4}-.1418206{col 67}{space 3} .1012857
{txt}{space 7}white {c |}{col 14}{res}{space 2} .2182497{col 26}{space 2} .0565915{col 37}{space 1}    3.86{col 46}{space 3}0.000{col 54}{space 4} .1070705{col 67}{space 3} .3294288
{txt}{space 5}college {c |}{col 14}{res}{space 2}-.0028717{col 26}{space 2} .0399751{col 37}{space 1}   -0.07{col 46}{space 3}0.943{col 54}{space 4}-.0814064{col 67}{space 3} .0756629
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4454786{col 26}{space 2} .0836781{col 37}{space 1}    5.32{col 46}{space 3}0.000{col 54}{space 4} .2810855{col 67}{space 3} .6098718
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
.         *Trust Officials
.         reg trustofficialbi military male age democrat republican white college

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       522
{txt}{hline 13}{c +}{hline 34}   F(7, 514)       = {res}    11.58
{txt}       Model {c |} {res} 16.5016824         7  2.35738321   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 104.611344       514  .203524016   {txt}R-squared       ={res}    0.1363
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1245
{txt}       Total {c |} {res} 121.113027       521  .232462623   {txt}Root MSE        =   {res} .45114

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}trustoffic~i{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}military {c |}{col 14}{res}{space 2} .2440008{col 26}{space 2} .0397137{col 37}{space 1}    6.14{col 46}{space 3}0.000{col 54}{space 4} .1659797{col 67}{space 3} .3220219
{txt}{space 8}male {c |}{col 14}{res}{space 2} .0666911{col 26}{space 2} .0413531{col 37}{space 1}    1.61{col 46}{space 3}0.107{col 54}{space 4}-.0145507{col 67}{space 3} .1479328
{txt}{space 9}age {c |}{col 14}{res}{space 2}  .048394{col 26}{space 2} .0124928{col 37}{space 1}    3.87{col 46}{space 3}0.000{col 54}{space 4} .0238507{col 67}{space 3} .0729373
{txt}{space 4}democrat {c |}{col 14}{res}{space 2} .1109518{col 26}{space 2}  .063976{col 37}{space 1}    1.73{col 46}{space 3}0.083{col 54}{space 4}-.0147349{col 67}{space 3} .2366384
{txt}{space 2}republican {c |}{col 14}{res}{space 2}-.0342286{col 26}{space 2} .0641246{col 37}{space 1}   -0.53{col 46}{space 3}0.594{col 54}{space 4}-.1602071{col 67}{space 3} .0917499
{txt}{space 7}white {c |}{col 14}{res}{space 2} .1599309{col 26}{space 2} .0586519{col 37}{space 1}    2.73{col 46}{space 3}0.007{col 54}{space 4} .0447041{col 67}{space 3} .2751578
{txt}{space 5}college {c |}{col 14}{res}{space 2}-.0133735{col 26}{space 2} .0414305{col 37}{space 1}   -0.32{col 46}{space 3}0.747{col 54}{space 4}-.0947673{col 67}{space 3} .0680204
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